Search NASA⌕ Search

SEARCH · Search NASA

Results for “pooling”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 415 records · Page 23
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Effect of Cooling Rate on Nano-Eutectic Formation in Laser Surface Remelted and Rare Earth Modified Hypereutectic Al-20Si Alloys

Laser Surface Remelting (LSR) was applied to arc-melted Al-20Si-0.2Sr, Al-20Si-0.2Ce, and Al-20Si hypereutectic alloys to refine microstructures. Experiments revealed that microstructures in the melt pool varied from fully eutectic to a mixture of Al dendrites and inter-dendritic eutectic. We calculated cooling rates using the Eagar-Tsai model and correlated cooling rates with characteristic microstructures, revealing that a cooling rate on the order of 104 K/s could lead to maximized fully eutectic microstructure morphology. Due to rapid solidification, the Si composition in the LSR eutectic was measured at 18.2 wt.%, higher than the equilibrium eutectic composition of 12.6 wt.%Si. Compared to Al-20Si, Ce addition had no significant effect on the volume fraction of the fully eutectic structure but refined Si fibers to approximately 30 nm in diameter. Sr addition did not further refine the diameter of eutectic Si fibers compared to Al-20Si but increased the volume fraction of the fully eutectic microstructure morphology. The refinement ratio (φ) of the Si fiber diameter from the bottom of the melt pool to the surface for the three alloys was similar, at around 28%. The established correlation between the cooling rate and the size and morphology of the microstructure within the melt pool will enable tailoring of the microstructure in laser-processed as well as deposited alloys for high strength and plasticity.

36 MATERIALS SCIENCE↗
DOE OSTI2024

The Effect of Interlayer Delay on the Heat Accumulation, Microstructures, and Properties in Laser Hot Wire Directed Energy Deposition of Ti-6Al-4V Single-Wall

Laser hot wire directed energy deposition (LHW-DED) is a layer-by-layer additive manufacturing technique that permits the fabrication of large-scale Ti-6Al-4V (Ti64) components with a high deposition rate and has gained traction in the aerospace sector in recent years. However, one of the major challenges in LHW-DED Ti64 is heat accumulation, which affects the part quality, microstructure, and properties of as-built specimens. These issues require a comprehensive understanding of the layerwise heat-accumulation-driven process–structure–property relationship in as-deposited samples. In this study, a systematic investigation was performed by fabricating three Ti-6Al-4V single-wall specimens with distinct interlayer delays, i.e., 0, 120, and 300 s. The real-time acquisition of high-fidelity thermal data and high-resolution melt pool images were utilized to demonstrate a direct correlation between layerwise heat accumulation and melt pool dimensions. The results revealed that the maximum heat buildup temperature of the topmost layer decreased from 660 °C to 263 °C with an increase to a 300 s interlayer delay, allowing for better control of the melt pool dimensions, which then resulted in improved part accuracy. Furthermore, the investigation of the location-specific composition, microstructure, and mechanical properties demonstrated that heat buildup resulted in the coarsening of microstructures and, consequently, the reduction of micro-hardness with increasing height. Extending the delay by 120 s resulted in a 5% improvement in the mechanical properties, including an increase in the yield strength from 817 MPa to 859 MPa and the ultimate tensile strength from 914 MPa to 959 MPa. Cooling rates estimated at 900 °C using a one-dimensional thermal model based on a numerical method allowed us to establish the process–structure–property relationship for the wall specimens. The study provides deeper insight into the effect of heat buildup in LHW-DED and serves as a guide for tailoring the properties of as-deposited specimens by regulating interlayer delay.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Texture Analysis of Inconel 718 with Different Modes During Single-Track Laser Surface Re-Melting

An in-depth understanding of the texture formation in melt pools allows for the modification of the surface layer microstructure and corresponding material properties, providing an opportunity to integrate laser surface re-melting into metal additive manufacturing. This study investigates crystallographic texture formation at different cooling rates in single melting tracks on the Inconel 718 (IN718) plate produced by laser surface re-melting. The cooling rate varies from 2.31 × 10 5 °C/s to 9.56 × 10 5 °C/s with the increase in scanning rates from 400 mm/s to 1200 mm/s, measured by recently developed real-time temperature monitoring of melt pools. Columnar grains are dominant, with distinct crystallographic textures forming in the melt pools. At a slower scanning speed, the keyhole mode shows three different textures forming at different depths (crystallographically layered structure), while, at a faster scanning speed, the conduction mode shows only random grain orientation. There are no pores/voids detected, and the columnar grain morphology and columnar grain width (8.6 μm to 12.4 μm) follow the analysis framework in terms of thermal gradient and solidification rate analysis. This implies that laser surface re-melting provides the potential to modify the surface structure from a random grain orientation to a crystallographically layered structure.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Surrogate Constructed Scalable Circuits ADAPT-VQE in the Schwinger model

Inspired by recent advancements of simulating periodic systems on quantum computers, we develop a new approach, (SC)$^2$-ADAPT-VQE, to further advance the simulation of these systems. Our approach extends the scalable circuits ADAPT-VQE framework, which builds an ansatz from a pool of coordinate-invariant operators defined for arbitrarily large, though not arbitrarily small, volumes. Our method uses a classically tractable ``Surrogate Constructed'' method to remove irrelevant operators from the pool, reducing the minimum size for which the scalable circuits are defined. Bringing together the scalable circuits and the surrogate constructed approaches forms the core of the (SC)$^2$ methodology. Our approach allows for a wider set of classical computations, on small volumes, which can be used for a more robust extrapolation protocol. While developed in the context of lattice models, the surrogate construction portion is applicable to a wide variety of problems where information about the relative importance of operators in the pool is available. As an example, we use it to compute properties of the Schwinger model - quantum electrodynamics for a single, massive fermion in $1+1$ dimensions - and show that our method can be used to accurately extrapolate to the continuum limit.

Gustafson, Erik [RIACS, Mtn. View] (ORCID:00000001↗
DOE OSTI2022

Data from: Land-based climate solutions for the United States

Meeting end-of-century global warming targets requires aggressive action on multiple fronts. Recent reports note the futility of addressing mitigation goals without fully engaging the agricultural sector, yet no available assessments combine both nature-based solutions (reforestation, grassland and wetland protection, and agricultural practice change) and cellulosic bioenergy for a single geographic region. Collectively, these solutions might offer a suite of climate, biodiversity, and other benefits greater than either alone. Nature-based solutions are largely constrained by the duration of carbon accrual in soils and forest biomass; each of these carbon pools will eventually saturate. Bioenergy solutions can last indefinitely but carry significant environmental risk if carelessly deployed. We detail a simplified scenario for the U.S. that illustrates the benefits of combining approaches. We assign a portion of non-forested former cropland to bioenergy sufficient to meet projected mid-century transportation needs, with the remainder assigned to nature-based solutions such as reforestation. Bottom-up mitigation potentials for the aggregate contributions of crop, grazing, forest, and bioenergy lands are assessed by including in a Monte Carlo model conservative ranges for cost-effective local mitigation capacities, together with ranges for (a) areal extents that avoid double counting and include realistic adoption rates and (b) the projected duration of different carbon sinks. The projected duration illustrates the net effect of eventually saturating soil carbon pools in the case of most strategies, and additionally saturating biomass carbon pools in the case of reforestation. Results show a conservative end-of-century mitigation capacity of 110 (57 – 178) Gt CO2e for the U.S., ~50% higher than existing estimates that prioritize nature-based or bioenergy solutions separately. Further research is needed to shrink uncertainties but there is sufficient confidence in the general magnitude and direction of a combined approach to plan for deployment now.

09 BIOMASS FUELS↗
DOE OSTI2023

Assessing carbon storage capacity and saturation across six central US grasslands using data–model integration

Abstract. Future global changes will impact carbon (C) fluxes and pools in most terrestrial ecosystems and the feedback of terrestrial carbon cycling to atmospheric CO2. Determining the vulnerability of C in ecosystems to future environmental change is thus vital for targeted land management and policy. The C capacity of an ecosystem is a function of its C inputs (e.g., net primary productivity – NPP) and how long C remains in the system before being respired back to the atmosphere. The proportion of C capacity currently stored by an ecosystem (i.e., its C saturation) provides information about the potential for long-term C pools to be altered by environmental and land management regimes. We estimated C capacity, C saturation, NPP, and ecosystem C residence time in six US grasslands spanning temperature and precipitation gradients by integrating high temporal resolution C pool and flux data with a process-based C model. As expected, NPP across grasslands was strongly correlated with mean annual precipitation (MAP), yet C residence time was not related to MAP or mean annual temperature (MAT). We link soil temperature, soil moisture, and inherent C turnover rates (potentially due to microbial function and tissue quality) as determinants of carbon residence time. Overall, we found that intermediates between extremes in moisture and temperature had low C saturation, indicating that C in these grasslands may trend upwards and be buffered against global change impacts. Hot and dry grasslands had greatest C saturation due to both small C inputs through NPP and high C turnover rates during soil moisture conditions favorable for microbial activity. Additionally, leaching of soil C during monsoon events may lead to C loss. C saturation was also high in tallgrass prairie due to frequent fire that reduced inputs of aboveground plant material. Accordingly, we suggest that both hot, dry ecosystems and those frequently disturbed should be subject to careful land management and policy decisions to prevent losses of C stored in these systems.

58 GEOSCIENCES↗
DOE OSTI2024

Modeling microbial carbon fluxes and stocks in global soils from 1901 to 2016

Abstract. Soil microbes play a crucial role in the carbon (C) cycle; however, they have been overlooked in predicting the terrestrial C cycle. We applied a microbial-explicit Earth system model – the Community Land Model-Microbe (CLM-Microbe) – to investigate the dynamics of soil microbes during 1901 to 2016. The CLM-Microbe model was able to reproduce the variations of gross (GPP) and net (NPP) primary productivity, heterotrophic (HR) and soil (SR) respiration, microbial (MBC) biomass C in fungi (FBC) and bacteria (BBC) in the top 30 cm and 1 m, and dissolved (DOC) and soil organic C (SOC) in the top 30 cm and 1 m during 1901–2016. During the study period, simulated C variables increased by approximately 12 PgC yr−1 for HR, 25 PgC yr−1 for SR, 1.0 PgC for FBC and 0.4 PgC for BBC in 0–30 cm, and 1.2 PgC for FBC and 0.7 PgC for BBC in 0–1 m. Increases in microbial C fluxes and pools were widely found, particularly at high latitudes and in equatorial regions, but we also observed their decreases in some grids. Overall, the area-weighted averages of HR, SR, FBC, and BBC in the top 1 m were significantly correlated with those of soil moisture and soil temperature in the top 1 m. These results suggested that microbial C fluxes and pools were jointly governed by vegetation C input and soil temperature and moisture. Our simulations revealed the spatial and temporal patterns of microbial C fluxes and pools in response to environmental change, laying the foundation for an improved understanding of soil microbial roles in the global terrestrial C cycle.

He, Liyuan↗
DOE OSTI2024

Diverse organic carbon dynamics captured by radiocarbon analysis of distinct compound classes in a grassland soil

Soil organic carbon (SOC) is a large, dynamic reservoir composed of a complex mixture of plant- and microbe-derived compounds with a wide distribution of cycling timescales and mechanisms. The distinct residence times of individual carbon components within this reservoir depend on a combination of factors, including compound reactivity, mineral association, and climate conditions. To better constrain SOC dynamics, bulk radiocarbon measurements are commonly used to trace biosphere inputs into soils and to estimate timescales of SOC cycling. However, understanding the mechanisms driving the persistence of organic compounds in bulk soil requires analyses of SOC pools that can be linked to plant sources and microbial transformation processes. Here, we adapt approaches, previously developed for marine sediments, to isolate organic compound classes from soils for radiocarbon ( 14 C) analysis. We apply these methods to a soil profile from an annual grassland in Hopland, California (USA), to assess changes in SOC persistence with depth (down to 1 m). We measured the radiocarbon values of water-extractable organic carbon (WEOC), total lipid extracts (TLEs), total hydrolyzable amino acids (AAs), and an acid-insoluble (AI) fraction from bulk and physically separated size fractions (< 2 mm, 2 mm–63 µm, and < 63 µm). Our results show that Δ 14 C values of bulk soil, size fractions, and extracted compound classes became more depleted with depth, and individual SOC components have distinct age–depth distributions that suggest distinguishable cycling rates. We found that AAs and TLEs cycle faster than the bulk soils and the AI fraction. The AI was the most 14 C-depleted fraction, indicating that it is the most chemically inert in this soil. Our approach enables the isolation and measurement of SOC fractions that separate functionally distinct SOC pools that can cycle relatively quickly (e.g., plant and microbial residues) from more passive or inert SOC pools (associated with minerals or petrogenic) from bulk soils and soil physical fractions. With the effort to move beyond SOC bulk analysis, we find that compound class 14 C analysis can improve our understanding of SOC cycling and disentangle the physical and chemical factors driving OC cycling rates and persistence.

58 GEOSCIENCES↗
DOE OSTI2024

Irreversible Trace Metal Binding to Goethite Controlled by the Ion Size

The dynamics of trace metals at mineral surfaces influence their fate and bioaccessibility in the environment. Trace metals on iron (oxyhydr)oxide surfaces display adsorption–desorption hysteresis, suggesting entrapment after aging. However, desorption experiments may perturb the coordination environment of adsorbed metals, the distribution of labile Fe(III), and mineral aggregation properties, influencing the interpretation of labile metal fractions. In this study, we investigated irreversible binding of nickel, zinc, and cadmium to goethite after aging times of 2–120 days using isotope exchange. Dissolved and adsorbed metal pools exchange rapidly, with half times <90 min, but all metals display a solid-associated fraction inaccessible to isotope exchange. The size of this nonlabile pool is the largest for nickel, with the smallest ionic radius, and the smallest for cadmium, with the largest ionic radius. Spectroscopy and extractions suggest that the irreversibly bound metals are incorporated in the goethite structure. Rapid exchange of labile solid-associated metals with solution demonstrates that adsorbed metals can sustain the dissolved pool in response to biological uptake or fluid flow. Trace metal fractions that irreversibly bind following adsorption provide a contaminant sequestration pathway, limit the availability of micronutrients, and record metal isotope signatures of environmental processes.

58 GEOSCIENCES↗
DOE OSTI2020

A Dynamic Reduction Network for Point Clouds

Classifying whole images is a classic problem in machine learning, and graph neural networks are a powerful methodology to learn highly irregular geometries. It is often the case that certain parts of a point cloud are more important than others when determining overall classification. On graph structures this started by pooling information at the end of convolutional filters, and has evolved to a variety of staged pooling techniques on static graphs. In this paper, a dynamic graph formulation of pooling is introduced that removes the need for predetermined graph structure. It achieves this by dynamically learning the most important relationships between data via an intermediate clustering. The network architecture yields interesting results considering representation size and efficiency. It also adapts easily to a large number of tasks from image classification to energy regression in high energy particle physics.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Quarterly Management Document – FY22, 3rd Quarter, Multi-pass Hybrid Laser Arc Welding of Alloy 740H

During the 3rd quarter of FY22, progress was made on modeling and simulation of deep penetration laser welding of Alloy 740H. Advances in the modeling of residual stress development arising from the calculated temperature field of the solidifying weld pool were made to understand the development of solidification cracking. Additionally, preliminary modeling of the temperature field within the weld pool of a wobbling laser heat source was performed. The maximum temperature of the weld pool was found to vary with time. These result will allow modeling of deep penetration laser welding using a wobbling laser to mitigate weld defects and cracking. Also, additional characterization of hybrid laser arc welds indicated that these welds were not defect-free as originally thought and the current HLA welds would not be acceptable under criteria outlined in the ASME Boiler and Pressure Vessel Code, Section IX. Therefore, additional welding trails with variation of the welding parameters and HLA welding configurations are required to produce welds acceptable under the Section IX criteria. It was shown that considerable reduction of HLAW defects had been achieved with each successive welding campaign. Therefore additional variation of HLAW parameters may still yield the desired defect-free welds, however, options for alternate HLAW configurations as well as plate preheating are outlined as contingency plans to obtain suitable welds. These additional (unplanned) HLAW trial may prevent subsequent milestones from being achieved within the original budget.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Support Vector Machines for Classification of Direct Energy Deposition Standoff Distance for Improved Process Control

A critical factor in the implementation of direct energy deposition is the ability to maintain the standoff distance between the nozzle and the build surface, as this influences powder capture efficiency and overall part quality. Due to process-related variations, layer height may vary, causing unintended variation in standoff distance and poor build quality. While prior work has utilized contact probing to qualify standoff distance during processing, in situ methods for qualification of standoff distance are of major interest. The present work seeks to understand efficacy of image-based methods for classifying standoff distance variation in real-time using support vector machines (SVMs). It was hypothesized that the size of the melt pool and the amount of spatter will have significant correlations with deviations in the standoff distance; thus, SVMs were used on a dataset that is comprised of morphological features of melt pool size and image entropy. The SVM model was used to classify melt pool images into categories according to standoff distance variation from nominal. K-folds cross validation was used to find the optimal hyperparameters for the SVM model. To understand the impact of the selected features on the classification performance and inference speed, multiple models were trained with differing numbers of included features. Results for classification score, inference time, and image preprocessing/feature extraction from these data are reported. The present results show that the SVM model was able to predict the standoff distance classification with an accuracy of 97 percent and a speed of 0.122 s per image, making it a viable solution for real-time control of standoff distance.

Klesmith, Zoe↗
DOE OSTI2024

Microchannel Geometries for Improved Heat Transfer with Low-GWP refrigerants

Due to efforts aimed at decarbonizing industries, the use of refrigerants with low global warming potential (GWP) is highly recommended in the air-conditioning and refrigeration sectors. Despite possessing low-GWP values of less than 150, hydrofluoroolefins (HFO) exhibit relatively lower heat transfer performance compared to conventional hydrofluorocarbons (HFC) under certain operating conditions. In contrast to HFCs, there is a high demand for enhanced surfaces to meet the needs of heat transfer systems utilizing low GWP refrigerants. Accordingly, this study analyzes the pool boiling performance of low-GWP refrigerants in microchannel geometries. The experiments were carried out at various heat flux levels on both smooth and enhanced surfaces. The pool boiling behavior of low-GWP refrigerant R1234yf was compared to that of R-134a refrigerant in terms of heat transfer coefficient and wall superheat. The results indicate that the heat transfer coefficients of the enhanced surface are significantly higher than those of the smooth surface. Furthermore, the microchannel geometry demonstrated a lower wall superheat compared to the smooth surface. Additionally, a visualization study was performed using a high-speed camera to understand the pool boiling mechanism of low-GWP refrigerants on both smooth and enhanced surfaces.

Murugan, Muneeshwaran↗
DOE OSTI2025

Sockeye Code Validation Against UNIST Heat Pipe - Poster - Internship 2025

Sockeye is an engineering level code being developed under the MOOSE framework for modeling heat pipes. A heat pipe is a sealed tube with a wick structure filled with a working fluid that transfers heat efficiently and passively via phase change of the working fluid. Heat applied to the evaporator end creates a pressure gradient which causes vapor to migrate to the condenser end where the vapor deposits its energy and condenses. Capillary force generated by the wick structure then draws the liquid back to the evaporator. A validation study was performed to compare the Sockeye code against data produced at the Ulsan National Institute of Standards and Technology for a slightly overfilled sodium heat pipe. The heat pipe was operated under natural convection cooling and a decreasing inactive length was observed. The experiment was modeled in Sockeye using the condenser pool model, the front non-condensable gas (NCG) model, and the mixture NCG model separately to reproduce the inactive length phenomenon. Also, a new capability was implemented in MOOSE to allow for conjugate heat transfer from the condenser based on the Churchill-Chu correlation for natural convection. The condenser pool model showed an increasing inactive length, demonstrating that the behavior was likely not caused by a pool of excess liquid. The front NCG model was able to show good agreement with the experiment, but it suffered convergence issues at the front. Finally, the mixture NCG model gave good results when the axial mesh was sufficiently refined. This work culminated in additions to the Sockeye documentation and a contribution to a journal article that will be published later. This poster is a summary of my work which I can take back to my university for presentation.

42 - ENGINEERING↗
DOE OSTI2026

Contrasting effects of glutamate and branched-chain amino acid metabolism on acid tolerance in a Castellaniella isolate from acidic groundwater

Groundwater acidification co-occurring with nitrate pollution is a common, global environmental health hazard. Denitrifying bacteria have been leveraged for the in situ removal of nitrate in groundwater. However, co-existing stressors—such as low pH—reduce the efficacy of biological removal processes. Castellaniella sp. str. MT123 is a complete denitrifier that was isolated from acidic, nitrate-contaminated groundwater. The strain grows robustly by nitrate respiration at pH < 6.0, completely reducing nitrate to dinitrogen gas. Genomic analyses of MT123 revealed few previously characterized acid tolerance genes. Thus, we utilized a combination of proteomics, metabolomics, and competitive mutant fitness to characterize the genetic mechanisms of MT123 acclimation to growth under mildly acidic conditions. We found that glutamate accumulation is critical in the acid acclimation of MT123, possibly through consumption of intracellular protons via glutamate decarboxylation to GABA. This is despite the fact that MT123 lacks the canonical glutamate decarboxylase-glutamate/GABA antiporter system implicated in acid tolerance in other bacteria. In contrast, branched-chain amino acid (BCAA) accumulation was detrimental to cell growth at lower pHs, possibly through indirect mechanisms impacting the cellular glutamate pool. Genetic analysis previously linked MT123 to a population of Castellaniella that bloomed—concurrent to nitrate removal—during a biostimulation effort to reduce groundwater nitrate concentrations at MT123’s location of origin. Thus, our analyses provide novel insight into mechanisms of acclimation to acidic conditions in a strain with significant potential for nitrate bioremediation.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

L-PBF High-Throughput Data Pipeline Approach for Multi-modal Integration

Abstract Metal-based additive manufacturing requires active monitoring solutions for assessing part quality. Multiple sensors and data streams, however, generate large heterogeneous data sets that are impractical for manual assessment and characterization. In this work, an automated pipeline is developed that enables feature extraction from high-speed camera video and multi-modal data analysis. The framework removes the need for manual assessment through the utilization of deep learning techniques and training models in a weakly supervised paradigm. We demonstrate this pipeline’s capability over 700,000 high-speed camera frames. The pipeline successfully extracts melt pool and spatter geometries and links them to corresponding pyrometry, radiography, and processparameter information. 715 individual prints are examined to reveal melt pool areas that exceeds 0.07 mm 2 and pyrometry signal over a threshold (375 pyrometry units) were more likely to have defects. These automated processes enable massive throughput of characterization techniques.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Nanoparticle-enabled increase of energy efficiency during laser metal additive manufacturing

The low energy efficiency of the laser metal additive manufacturing (AM) process is a potential sustainability concern for large-scale industrial production. Explicit investigation of the energy efficiency for laser melting requires the direct characterization of melt pool dimension and vapor depression, which is very difficult due to the opaque nature of the molten metal. Here we report the direct observation and quantification of effects of the TiC nanoparticles on the vapor depression and melt pool formation during laser powder bed fusion (LPBF) of Al6061 by in-situ high-speed high-energy x-ray imaging. Based on the quantification results, we calculated the laser melting energy efficiency (defined here as the ratio of the energy needed to melt the material to the energy delivered by the laser beam) with and without TiC nanoparticles during LPBF of Al6061. Here the results show that adding TiC nanoparticles into Al6061 leads to a significant increase of laser melting energy efficiency (114% increase on average, 521% increase under 312 W laser power, 0.4 m/s scan speed). Systematic property measurement, simulation, and x-ray imaging studies enable us, for the first time, to identify that three mechanisms work together to enhance the laser melting energy efficiency: (1) adding TiC nanoparticles increases the absorptivity; (2) adding TiC nanoparticles decreases the thermal conductivity, and (3) adding TiC nanoparticles enables the initiation of vapor depression and multiple reflection at lower laser power (i.e., lowers the laser power threshold for keyholing). The method and mechanisms of using TiC nanoparticles to increase the laser melting energy efficiency during LPBF of Al6061 we reported here may guide the development of feedstock materials for more energy efficient laser metal AM.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Investigation of the Sensitivity of Tropical Cyclogenesis to Aerosol Intervention

Abstract As risks from tropical cyclones (TCs) are fueled by climate change escalation, there is an urgent need for transformational solutions to complement traditional approaches. Seeding TCs using aerosols can be a promising method to reduce cyclone intensity, supported by theoretical understanding of the microphysical effects of aerosols on TC clouds. The ideal time to intervene effectively in TCs is likely during their initial stage, before TC wind speeds reach their peak. However, studies exploring potential aerosol effects on TC formation remain scarce. This study investigates how a TC embryo responds to the addition of aerosols of varying sizes using the Weather Research & Forecasting (WRF) model coupled with a spectral‐bin microphysics model. We found that aerosols of different sizes and concentrations distinctively affect the pre‐TC vortex's microstructure and dynamics. Fine and ultrafine aerosols enhance the latent heat of condensation, freezing, deposition, and riming, initially intensifying the vortex. However, this results in enhancement of the cold pool, thereby reducing inflow and surface fluxes, subsequently weakening the vortex. Coarse aerosols produce the opposite effect to that of fine and ultrafine aerosols. Coarse aerosols lead to a slower initial acceleration owing to enhanced warm rain. However, the resulting weaker cold pool is insufficient to effectively reduce the strength of the vortex at the later stage. This study provides critical insights into how aerosols of varying sizes and concentrations modulate the energy cascade and impact the evolution of a TC embryo, laying the groundwork for further research on TC risk management through aerosol intervention.

54 ENVIRONMENTAL SCIENCES↗