Small Fluctuations Research Articles

Explorative Binary Gray Wolf Optimizer with Quadratic Interpolation for Feature Selection.

The high dimensionality of large datasets can severely impact the data mining process. Therefore, feature selection becomes an essential preprocessing stage, aimed at reducing the dimensionality of the dataset by selecting the most informative features while improving classification accuracy. This paper proposes a novel binary Gray Wolf Optimization algorithm to address the feature selection problem in classification tasks. Firstly, the historical optimal position of the search agent helps explore more promising areas. Therefore, by linearly combining the best positions of the search agents, the algorithm's exploration capability is increased, thus enhancing its global development ability. Secondly, the novel quadratic interpolation technique, which integrates population diversity with local exploitation, helps improve both the diversity of the population and the convergence accuracy. Thirdly, chaotic perturbations (small random fluctuations) applied to the convergence factor during the exploration phase further help avoid premature convergence and promote exploration of the search space. Finally, a novel transfer function processes feature information differently at various stages, enabling the algorithm to search and optimize effectively in the binary space, thereby selecting the optimal feature subset. The proposed method employs a k-nearest neighbor classifier and evaluates performance through 10-fold cross-validation across 32 datasets. Experimental results, compared with other advanced algorithms, demonstrate the effectiveness of the proposed algorithm.

Trajectories of procrastination among Swedish University students over one academic year: a cohort study

BackgroundProcrastination is common among university students and associated with adverse outcomes such as physical and mental health problems. According to the Temporal motivation theory procrastination may vary over time depending on the temporal proximity to goals and deadlines.AimsTo determine if mean procrastination levels among university students varies over an academic year, and if trajectories of procrastination are moderated by gender identity, perfectionistic strivings, and/or perfectionistic concerns.SampleSwedish university students (n = 1410).MethodsThe cohort was followed with web-surveys at four time-points over one academic year (Late semester, Mid semester, After semester, and Early semester). Generalized Estimating Equations were used to estimate mean levels of self-rated procrastination at the different time-points.ResultsWe found only small fluctuations in mean procrastination levels over the academic year. Participants with high perfectionistic concerns demonstrated higher mean procrastination levels at all time-points, but neither gender identity, perfectionistic concerns nor perfectionistic strivings affected the slope of the mean procrastination trajectories.ConclusionsIn this cohort of Swedish university students, self-rated procrastination levels were stable over the academic year. Perfectionistic concerns, but not gender identity or perfectionistic strivings, was associated with higher levels of procrastination.

Application of a GIS-Based Multi-Criteria Decision-Making Approach to the Siting of Ocean Thermal Energy Conversion Power Plants: A Case Study of the Xisha Sea Area, China

In order to achieve the goals of carbon neutrality and reduced carbon emissions, China is increasingly focusing on the development and utilization of renewable energy sources. Among these, ocean thermal energy conversion (OTEC) has the advantages of small periodic fluctuations and large potential reserves, making it an important research field. With the development of the “Maritime Silk Road”, the Xisha Islands in the South China Sea will see a growing demand for electricity, providing the potential for OTEC development in this region. Optimal site selection of OTEC power plants is a prerequisite for developing thermal energy provision, affecting both the construction costs and future benefits of the power plants. This study establishes a scientific evaluation model based on the decision-making frameworks of geographic information systems (GISs) and multi-criteria decision-making (MCDM) methods, specifically the analytic hierarchy process (AHP) for assigning weights, the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) to reclassify the factors, and weighted linear combination (WLC) to compute the suitability index. In addition to commonly considered factors such as temperature difference and marine usage status, this study innovatively incorporates geological conditions and maximum offshore distances of cold seawater based on cost control. The final evaluation identifies three suitable areas for OTEC development near the Xuande Atoll and the Yongle Atoll in the Xisha Sea Area, providing valuable insights for energy developers and policymakers.

Quantifying the ultimate limit of plasmonic near-field enhancement

Quantitatively probing the ultimate limit of near-field enhancement around plasmonic nanostructures remains elusive, despite more than five decades since the discovery of surface-enhanced Raman scattering. Theoretical calculations have predicted an ultimate near-field enhancement exceeding 1000 using the best plasmonic material silver, but experimental estimations disperse by orders of magnitude. Here, we design a high-quality silver plasmonic nanocavity with atomic precision and precisely quantify the upper limit of near-field enhancement in ~1 nm junctions. A hot-spot averaged Raman enhancement of 4.27 × 1010 is recorded with a small fluctuation, corresponding to an averaged electric field enhancement larger than 1000 times. This result quantitatively delineates the ultimate limit of plasmonic field enhancement around plasmonic nanostructures, establishing a foundation for diverse plasmon-enhanced processes and strong light-matter interactions at the atomic scale.

A “self-driven” roving membrane with enhanced water-pumping and dye rejection performance

Considering that traditional membrane treatment of dyeing wastewater requires extra driving pressure, this work successfully prepared a roving membrane powered by the siphoning and wicking effects of the roving to separate dyes from dyeing wastewater. In this work, we found that bamboo pulp roving had the optimal siphoning and wicking performance, making it the focus for subsequent research. At the optimized interfacial polymerization parameters, the prepared roving membrane exhibited the optimal water-pumping and dye rejection performance, which reached 9.11 g/h and 99.58 %, respectively. The diameter of the rovings wrapped in polyamide layer became smaller and the wicking performance was improved. In addition, the thickness of polyamide layer with uniformly distributed nanoTiO2 decreased, and the crosslinking degree was enhanced. Ultraviolet light further contributed to the enhanced water-pumping and dye rejection performance of the piperazine/TiO2/trimesoyl chloride roving membrane. During the 120-h continuous filtration, the water-pumping and rejection performance was stable with only small fluctuations. Importantly, high dye retentions and water-pumping rate were achieved. In this study, we successfully prepared a membrane that is easy to use and does not require extra driving pressure, providing a new approach for dye wastewater treatment.

Elite women's soccer match demand can be described using complexity-based analyses and multifractals

The present study aimed to investigate the variability of the displacements in elite women soccer players during official matches according to the position of the players and to the match progression using non-linear analyses (entropy and multifractal spectrum).Sixty-three velocity profiles from global positioning devices of elite professional women soccer players were analyzed. The mean, coefficient of variation, and maximum velocity were calculated during the match using four equal segments. Sample entropy and seven parameters derived from the multifractal detrended fluctuation analysis were also calculated. The players were split into five field playing positions: forwards (FW), offensive midfielders (OM), defensive midfielders (DM), central defenders (CD), and lateral defenders (LD).No significant playing position × period interaction was found for the different parameters analyzed. However, most parameters showed a significant main effect for playing position (p < .01) and period (p < .01). Compared to the other players, FW and OM have the lowest entropy. All players showed a dominance of small velocity fluctuations but FW players showed the widest multifractal spectrum primarily. In contrast, CD had a narrow spectrum and reduced amount of small fluctuations. As the game progressed, mean velocity and entropy significantly decreased. In contrast, the multifractal peak value significantly alongside with changes in asymmetry.From the present results, velocity profiles during elite women's soccer games depicted multifractal features sensitive to player position and match segment, which can help to understand the dynamics and variability of players' responses during a match.

Retrieval of total suspended matter concentration in the yellow river estuary offshore area based on QAA-RF model

ABSTRACT Total suspended matter is one of the crucial water quality parameters for both inland and marine environments, and a key role in evaluating the water quality of estuaries and offshore areas. Each year, the Yellow River carries a significant amount of sediment into the semi-enclosed Bohai Sea, results in a prolonged high concentration of total suspended matter in the offshore areas of the Yellow River Estuary. This study focuses on the offshore region of the Yellow River Estuary in China. Utilizing Sentinel-2 satellite imagery data from 2020 to 2023 and in-situ measured data from August 2020 to August 2022, to address the lack of physical mechanisms currently studied in machine learning retrieval methods, a model that integrates the physics-driven Quasi-Analytical Algorithm (QAA) and data-driven Random Forest (RF) is employed for the retrieval of total suspended matter concentration in the study area. The fused model (QAA-RF) is compared and analysed against regression models and standalone machine learning models. The results indicate that the accuracy of machine learning retrieval models is consistently higher than that regression models. The QAA-RF model demonstrates the highest accuracy (R 2 = 0.87, MAE = 5.01 mg L−1, RMSE = 6.39 mg L−1). Based on the QAA-RF model and the imagery data, monthly total suspended matter concentration is conducted in the study area. The retrieval results indicates that: (1) the total suspended matter concentrations is primarily concentrated in the near estuary region, with concentrations decreasing as distance from the estuary increases. (2) the total suspended matter concentration exhibits a distribution pattern with higher values in spring and winter, and lower values in summer and autumn. (3) the concentration of total suspended matter shows relatively small fluctuations at the annual scale from 2020 to 2023.

Modelling Newtonian noise of vibroacoustic origin in the Virgo gravitational wave detector

With ~100 detections by the LIGO-Virgo-KAGRA network, gravitational astronomy has definitely begun. The Virgo detector is a modified Michelson interferometer with two arms of 3km each, made of optical resonator housing ~100 kW laser beams. It can measure a gravitational strain (ΔL/L) of ~10^(-21). The detector is susceptible to various sources of noise within specific frequency bands. Among these, the "Newtonian" or "gravity-gradient" noise (seismic and atmospheric/acoustic) could limit the low-frequency sensitivity (below a few tens of Hz) of LIGO and Virgo as they reach their full sensitivity, as well as that of next-generation detectors such as the European Einstein Telescope and the US Cosmic Explorer. This paper focuses on modeling Newtonian noise of acoustic origin, which refers to the small fluctuations in the gravity field resulting from the acoustic field present in the experimental halls. The fluctuating gravitational field directly causes random forces on sensitive optical elements, such as the interferometer test masses. The induced noise is quantified using a numerical acoustic model of the experimental room when it is excited by the air conditioning system.

Multi-objective optimization of HESS control for optimal frequency regulation in a power system with RE penetration

Concerns over fossil fuel emissions and their hazardous effects have led to a shift away from conventional power plants and focus more on the expansion of renewable energy sources. This shift has resulted in reduced inertia and resulted in poor frequency control within electrical power systems. Hybrid Energy Storage Systems (HESS) have been proposed as an effective solution to enhance frequency stability and address the reduced inertia issue. This research evaluates three distinct control models for HESS, Incorporating Supercapacitor Energy Storage (SCES) and Battery Energy Storage Systems (BESS). To optimize the control parameters with the best objectives, all possible sets of objectives with four different optimization algorithms are studied. The three control models considered for the HESS incorporate Virtual Synchronous Generator (VSG) or Virtual Inertia (VI) control with independent or simultaneous optimization of control parameters. The performances of the three control models are evaluated based on three test scenarios incorporating uncertainties, reduced inertia, and uniform and random load disturbances. The findings indicate that the Independently Optimized Virtual Synchronous Generator HESS (IO VSG-HESS) achieves the best settling time post-contingency but offers the least improvement in frequency nadir with an average of 0.31 %. Conversely, the Simultaneously Optimized Virtual Inertia And Virtual Synchronous Generator Controlled HESS (SO VI-VSG-HESS) excel in mitigating small frequency fluctuations with an average improvement in frequency standard deviation of 87.65 %. The Simultaneously Optimized Virtual Synchronous Generator Controlled HESS (SO VSG-HESS) provides the best frequency nadir, with an average improvement of 0.63 %, but with a slight increase in settling time.

Aspects of Everpresent Λ. Part II. Cosmological tests of current models

This paper investigates Everpresent Λ, a stochastic dark energy model motivated by causal set theory and unimodular gravity, and confronts it with two key observational data sets, Supernova Ia (SN Ia) and Cosmic Microwave Background (CMB) data. A key feature of this model is that Λ fluctuates over time and on average the magnitude of its fluctuations is of the order of the dominant energy density (be it radiation or matter) for the given epoch. In particular, we focus on a phenomenological implementation of Everpresent Λ known as Model 1. The random fluctuations in Everpresent Λ realizations are generated using seed numbers, and we find that for a small fraction of seeds Model 1 is capable of producing realizations that fit SN Ia data better than ΛCDM. We further investigate what features distinguish these realizations from the more general behaviour, and find that the “good” realizations have relatively small fluctuations at low redshifts (z < 1.5), which do not closely track the matter density. We find that Model 1 struggles to improve on ΛCDM at describing the CMB data. However, by suppressing the values of Λ near the last scattering surface, as suggested in [1], we find a large improvement in the best fit of the model, though still with a χ 2 value much larger than that of ΛCDM. We also study the allowed variation of the dark energy density by the CMB constraints in a more model-independent manner, and find that some variation (especially prior to recombination) is possible and in fact can lead to improvement over ΛCDM and reduce the Hubble tension, in line with some early dark energy proposals. However, for the kinds of variations considered, the favoured fluctuations are smaller in magnitude than is typical in current Everpresent Λ models.

In Silico Screening of FDA‐Approved Anthelmintic Drugs Against LuxR Protein as Quorum‐Sensing Inhibitors and Exploration of Their Binding Mechanism and Electronics Properties

AbstractTreating bacterial infections triggered by multidrug‐resistant bacteria is a global priority. Issue of multidrug resistance can be managed by inhibiting bacterial quorum sensing mechanism. Quorum‐sensing inhibitors (QSIs) are promising alternatives to antibiotics. Herein, a library of FDA‐approved anthelmintic medications was screened using in silico techniques for LuxR protein associated with the quorum‐sensing (QS) mechanism of Staphylococcus aureus. Drug repurposing can reduce the time and financial risk of drug development. Seven FDA‐approved drugs (Fenbendazole, Mebendazole, Flubendazole, Praziquantel, Oxyclozanide, Rafoxanide, and Albendazole) showed strong binding affinity to the LuxR protein with binding free energy less than −6.00 kcal/mol. Molecular dynamic simulation (100 ns) of the docked complexes revealed that Fenbendazole and Rafoxanide remain at the binding pocket of the LuxR protein most of the time. During the whole simulation period, backbone of all seven complexes displayed small fluctuation in the RMSD and Rg. The free energy landscape of LuxR–Rafoxanide and LuxR–Fenbendazole complexes showed promising stability compared to the rest of the complexes. Both the complexes showed excellent MMPBSA binding free energy: −92.882 ± 15.636 kJ/mol (LuxR–Rafoxanide) and −74.873 ± 9.233 kJ/mol (LuxR–Fenbendazole). The reactivity of the ligands was ascertained from their DFT‐based various descriptors.

Dispersion and particle pressure in sedimenting suspensions with hydrodynamic interactions and nonzero particle inertia

Particle inertia is a feature of suspension dynamics that is often neglected. However, its neglect changes the order of the governing equations of particle motion. In this work, we examine the impact of the inertia of particles over their velocity fluctuations and the resulting stresses. In order to observe effects of particle inertia, we consider dusty-gas suspensions of spherical weakly Brownian microparticles sedimenting in a Newtonian fluid at low Reynolds numbers. We first investigate the motion of a single spherical particle. The simulations for this simple case allow us to define the appropriate physical parameters of the flow and to validate the numerical calculation of velocity statistics over a range of Péclet and Stokes numbers. Next, we perform Langevin dynamics simulations with periodic boundary conditions to integrate the equations governing the translational and rotational motions of N hydrodynamically interacting particles suspended in the viscous fluid. The first aim of this paper is to examine the behavior of the velocity variance of inertial particles, with small fluctuations produced by Brownian motion at the moderate Péclet numbers. The interplay between mild Brownian forces and hydrodynamic interactions decreases the anisotropy of velocity fluctuations observed in non-Brownian suspensions (Pe≫1) of sedimenting particles. The simulation results suggest that particle inertia attenuates the magnitude of velocity fluctuations produced by both Brownian motion and viscous hydrodynamic interactions. Additionally, we study the long-time behavior of the velocity fluctuations by calculating their autocorrelation functions and the particle diffusivities. The numerical simulations show clear evidence of particle pressure arising from the flow disturbance produced by hydrodynamic interactions in a suspension. From the particle velocity variance obtained in the present numerical simulations, we propose a simple model for particle-phase pressure as a linear function of the particle volume fraction ϕ⩽5%, which is usually a closure quantity required in models of more complex particulate systems such as fluidized beds.

The giant graviton expansion in $AdS_5 \times S^5$

The superconformal index of \frac1212-BPS states of \mathcal{N}=4𝒩=4U(N)U(N) super Yang-Mills theory has a known infinite qq-series expression with successive terms suppressed by q^NqN. We derive a holographic bulk interpretation of this series by evaluating the corresponding functional integral in the dual AdS_5 × S^55×S5. The integral localizes to a product of small fluctuations of the vacuum and of the collective modes of an arbitrary number of giant-gravitons wrapping an S^3S3 of maximal size inside the S^5S5. The quantum mechanics of the small fluctuations of one maximal giant is described by a supersymmetric version of the Landau problem. The quadratic fluctuation determinant reduces to a sum over the supersymmetric ground states, and precisely reproduces the first non-trivial term in the infinite series. Further, we show that the terms corresponding to multiple giants are obtained precisely by the matrix versions of the above super-quantum-mechanics.

Elucidating the effects of metal transfer modes and investigating the material properties in wire-arc additive manufacturing (WAAM)

AbstractStudies have shown the influence of WAAM process parameters on mechanical properties, bead formation, dimensional accuracy, and microstructure. However, metal transfer modes and their interactions with input variables have not been investigated thoroughly. Therefore, short/spray, pulse and double pulse modes were investigated in this study at different current levels. Bead-on-plate trials were conducted by depositing ER70S-6 wire to investigate bead morphology, dilution, microstructure, and hardness. The study was supported by a detailed statistical approach, including analysis of variance (ANOVA) and regression analysis. Similarly, the combined effects of hatch distance and current were studied on bead formation in multi-layer deposits. Moreover, a thin wall and a cubic structure were deposited to realize the WAAM capability for larger depositions. The microstructures of thin wall and cubic structure were analyzed using optical microscopy (OM) and scanning electron microscopy (SEM). The study concludes that metal transfer modes at various currents significantly influence bead geometry, microstructure and hardness. The microstructure of bead-on-plate trials show fine lamellar structure at low current in all modes. Higher current results in coarse grains with a polygonal and columnar morphology. The hardness shows a decreasing trend as the current increases. The combined effects of current and hatch distance alter bead morphology; however, an optimized combination yields smoother surfaces. The microstructure of thin wall showed a slight anisotropy along the building direction. The presence of small pores was witnessed from OM and SEM images. Similarly, the cubic structure showed a more homogeneous microstructure with much lower porosity. The hardness profile of the thin wall exhibited small fluctuations along the building direction, while that of the cubic structure was more uniform.

Joint Model Parameter Identification and EKF Algorithm for the SOC Estimation of LFP Battery

Abstract Accurately estimating the state of charge (SOC) of batteries is crucial for achieving the safety and efficient driving of electric vehicles. To address the negative impact of voltage platform flatness and accumulated errors in current sampling, the SOC estimation method jointing model parameter identification and extended Kalman filter (EKF) algorithm is proposed and verified through simulation in this paper. Firstly, the parameter identification method is obtained based on the second-order dual polarization model, and effective identification of the parameters under different SOC is achieved using experimental conditions of hybrid pulse power characteristic and constant current discharge. On this basis, a function model with SOC as the independent variable and model parameters as the dependent variable is established by jointing model parameter identification and EKF algorithm, and the iterative estimation of SOC is achieved through the 1stopt and cftool methods. Finally, the SOC estimation accuracy of the proposed method is validated under three operating conditions that adopt the latest standards and are closer to the actual driving environment. The simulation results show that the SOC estimation method jointing model parameter identification and EKF algorithm has higher accuracy and smaller fluctuations than the traditional AH integration method, and the mean squared error (MSE) of estimation for the four test conditions are less than 0.29%, 0.72% and 0.25%, respectively.

Performance analysis of a high-frequency two-stage proportional valve piloted by two high-speed on/off valve arrays

Two-stage proportional valves (TSPV) have been used extensively for electro-hydraulic control systems with large-flow applications. Due to the inherent characteristics of the pilot spool, such as hysteresis, motion quality, and dead zone, the dynamic performance of the traditional TSPV cannot be further improved. To solve this issue, this paper proposes a high-frequency two-stage proportional valve (HFTSPV) piloted by two high-speed on/off valve arrays, which integrates the advantages of dual nozzle flapper mechanism and parallel-connected valve technology. First, an entire mathematical model is established, in which some key parameters are estimated by experiments, such as the actual diameters and flow coefficients of orifices, and flow coefficient of pilot valve. Then, the influences of fixed orifices with different diameters on the dynamic characteristics of main spool are explored. Subsequently, the optimal diameter of fixed orifice is calculated theoretically by using the maximum pressure sensitivity and flow linearity, aiming to realize the high dynamic and small displacement fluctuation. Finally, step and sinusoidal tracking experiments show that the delay time of the HFTSPV is close to 3.3 ms, and the displacement fluctuation decreases with the increase of tracking frequency. Amplitude–frequency results indicate that −3 dB frequency of the HFTSPV reaches 16 Hz under ±50% full scale and 30 Hz under 0% –50% full scale.

Impact of climate change on the geographical distribution of ticks of public health significance in Colombia: Amblyomma ovale (Ixodida: Ixodidae), the Amblyomma maculatum (Ixodida: Ixodidae) complex and the Amblyomma cajennense (Ixodida: Ixodidae) complex

Abstract Ticks of the Amblyomma maculatum (Ixodida Ixodidae) complex, the Amblyomma cajennense (Ixodida Ixodidae) complex and Amblyomma ovale (Ixodida Ixodidae) are known to transmit various Rickettsia species in Colombia, but their exact distribution is unknown. We built several models based on current climate and projected future climate changes using a maximum entropy approach. A total of 314 records of the A. cajennense complex (65.9%; n = 207), A. ovale (22.9%; n = 72), and the A. maculatum complex (11.1%; n = 35) were obtained. Amblyomma ovale has a current distribution in the Pacific, Caribbean and Andean regions and could be potentially found in the Amazon. Amblyomma maculatum has a current distribution in the Andean and could potentially be found in the Caribbean and Orinoco regions. Amblyomma mixtum can be found near the Caribbean Sea and in the Pacific region, and A. patinoi is likely to be found in the Andean region and the Caribbean. In 2070, it will be possible to find an expansion of A. ovale and A. maculatum and a decrease of A. mixtum and A. patinoi. The variables that best predict the distribution of these species are isothermality (small fluctuations in temperature) and annual precipitation. Amblyomma cajennense s.l and A. ovale, A. cajennese s.l and A. patinoi, as well as A. maculatum and A. patinoi, have an important environmental sympatry. Epidemiological and acarological surveillance is crucial to investigate rickettsiosis caused by R. parkeri in A. ovale regions, by R. rickettsii in A. patinoi and A. mixtum areas, and by R. parkeri s.s in A. maculatum regions.

Evaluation of urban low-carbon development efficiency: evidence from 30 cities in China

With the acceleration of global urbanization, the issues faced by urban development are becoming increasingly apparent. Some countries and regions have placed less emphasis on low-carbon emissions in the development process and prioritized urban development. However, blindly pursuing rapid urbanization has led to excessive urban carbon emissions, which outweigh the gains. Therefore, based on panel data from 30 cities in China from 2010 to 2019, this study combines the super-efficiency slacks-based measure (SBM) model and the Malmquist index, taking urban carbon emissions as undesirable outputs, to evaluate urban development efficiency. Through a multidimensional comparative analysis, this study reveals the developmental challenges encountered by various cities. The results show that: statically, the overall urbanization progress of these 30 cities is commendable, but significant fluctuations are observed in the development trend. The mean super-efficiency of cities in the eastern coastal areas is relatively high, whereas other regions exhibit instances of ineffective mean super-efficiency. Dynamically, there are few periods of efficiency improvement during 2010–2019, and there is an imbalance in the sources of efficiency improvement. Shanghai and Hangzhou exhibit the best continuous dynamic improvement status, with small fluctuations in dynamic efficiency, whereas Guiyang has the worst dynamic efficiency improvement status, indicating poor urban development. This study underscores the urgent need for a balanced approach to urban development that incorporates low-carbon initiatives to ensure sustainable progress and mitigate adverse environmental impacts.

VIBRATIONS OF A VERTICAL BEAM ROTATING WITH VARIABLE ANGULAR VELOCITY

An Euler-Bernoulli beam in vertical position rotating about its symmetry axis along its length is considered. The angular velocity is assumed to have small fluctuations about a constant mean velocity. The partial differential equation of motion is derived first. The equation is cast into a non-dimensional form. The natural frequencies are calculated for the pinned-pinned case. Principle parametric resonances such that the fluctuation frequency being close to two times one of the natural frequencies are considered. By employment of the Method of Multiple Scales, an approximate perturbation solution is found. The frequency response diagrams are drawn and the bifurcation points for transition from the trivial solution to the non-trivial solution are calculated. The conditions for which such resonances occur are exploited in the numerical results.

Cavitating Bubbles in Condensing Gas as a Means of Forming Clumps, Chondrites, and Planetesimals

Vaporized metal, silicates, and ices on the verge of recondensing into solid or liquid particles appear in many contexts: behind shocks, in impact ejecta, and within the atmospheres and outflows of stars, disks, planets, and minor bodies. We speculate that a condensing gas might fragment, forming overdensities within relative voids, from a radiation–condensation instability. Seeded with small thermal fluctuations, a condensible gas will exhibit spatial variations in the density of particle condensates. Regions of higher particle density may radiate more, cooling faster. Faster cooling leads to still more condensation, lowering the local pressure. Regions undergoing runaway condensation may collapse under the pressure of their less condensed surroundings. Particle condensates will compactify with collapsing regions, potentially into macroscopic bodies (planetesimals). As a first step toward realizing this hypothetical instability, we calculate the evolution of a small volume of condensing silicate vapor—a spherical test “bubble” embedded in a background medium whose pressure and radiation field are assumed fixed for simplicity. Such a bubble condenses and collapses upon radiating its latent heat to the background, assuming that its energy loss is not stopped by background irradiation. Collapse speeds can range up to sonic, similar to cavitation in terrestrial settings. Adding a noncondensible gas like hydrogen to the bubble stalls the collapse. We discuss whether cavitation can provide a way for millimeter-sized chondrules and refractory solids to assemble into meteorite parent bodies, focusing on CB/CH chondrites whose constituent particles likely condensed from silicate/metal vapor released from the most energetic asteroid collisions.