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At least 37 records · Page 2

Modeling shock-induced void collapse in single-crystal Ta systems at the mesoscales

Understanding the role of microstructural heterogeneities on the shock wave propagation and defect evolution behavior is essential to predicting the dynamic response of metals. Heterogeneities, such as voids, provide challenges to understanding the wave propagation behavior as the shock-void interaction can collapse the void and result in large plastic strains and significant heating (hot spot formation) in the metal. Accurate modeling of this phenomenon requires predicting the void collapse mechanisms and the related heat generation and dissipation mechanisms (hotspot formation) that determine the microstructure evolution. While molecular dynamics (MD) simulations can model the void collapse behavior, the time/length scale capabilities pose a challenge to connect with continuum models or the experimental scales. Here, this study presents the capability of the newly developed quasi-coarse-grained dynamics (QCGD) method that extends the MD simulations to larger system sizes and longer times to model this phenomenon. This study uses QCGD simulations to investigate the mechanisms of shock wave interactions with pre-existing voids in single-crystal Ta microstructures for variations in shock pressures, void size, and loading orientations. For a given orientation, the plasticity contributions and rates of void collapse are observed to vary with shock pressures and void size. The larger void sizes and higher pressures result in increased temperatures (hot spots) and faster void collapse rates and unravel the variations in the plasticity contributions. In addition, QCGD simulations investigate the post-collapse microstructure evolution as a release wave travels through the hot spot region. The simulations reveal that the reduction in temperatures due to heat dissipation initiates the dynamic recrystallization behavior in the hotspot regions.

36 MATERIALS SCIENCE↗

Exemption of lattice collapse in Ni–MnO 2 birnessite regulated by the structural water mobility

Lattice collapse and associated mechanical fracture frequently occur in Li-intercalated metal oxide cathodes at the deep charge state upon Li-ion removal, governed by chemical compositions and the resulting electron density of the oxygen atoms. However, similar lattice collapse for metal oxide electrodes in aqueous storage and its mitigation have not been well studied. In this work, we reported the lattice collapse of MnO 2 layered birnessite during the aqueous de-sodiation process at high voltage due to the structural water motion, as evidenced by in situ XRD. Unlike non-aqueous Li-intercalated electrodes, Ni-dopants mitigated the lattice collapse of birnessite at deep charge states. Moreover, density functional theory (DFT) calculations showed that Ni doping induces charge depletion of lattice oxygen due to its higher electronegativity than Mn. This charge reduction, in turn, yields a significant decrease in electrostatic repulsion between the oxygens belonging to lattice and structural water. Classical molecular dynamics simulations based on atomic charges obtained from DFT elucidate that Ni-doping facilitates immobilization of structural water in (Ni)MnO 2 and prevents lattice collapse upon Na-ion removal. (Ni)MnO 2 exempted from lattice collapse shows an improved storage capacity relative to MnO 2 while maintaining similar cycling stability.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Three-dimensional Hydrodynamic Simulations of Convective Nuclear Burning in Massive Stars Near Iron Core Collapse

Nonspherical structure in massive stars at the point of iron core collapse can have a qualitative impact on the properties of the ensuing core-collapse supernova explosions and the multimessenger signals they produce. Strong perturbations can aid successful explosions by strengthening turbulence in the postshock region. Here we report on a set of 4π 3D hydrodynamic simulations of O- and Si-shell burning in massive star models of varied initial masses using MESA and the FLASH simulation framework. We evolve four separate 3D models for roughly the final 10 minutes prior to and including iron core collapse. We consider initial 1D MESA models with masses of 14, 20, and 25 M ⊙ to survey a range of O/Si-shell density and compositional configurations. Further, we characterize the convective shells in our 3D models and compare them to the corresponding 1D models. In general, we find that the angle-average convective speeds in our 3D simulations near collapse are three to four times larger than the convective speeds predicted by MESA at the same epoch for our chosen mixing length parameter of α MLT = 1.5. In three of our simulations, we observe significant power in the spherical harmonic decomposition of the radial velocity field at harmonic indices of ℓ = 1–3 near collapse. Our results suggest that large-scale modes are common in massive stars near collapse and should be considered a key aspect of presupernova progenitor models.

79 ASTRONOMY AND ASTROPHYSICS↗

Core-collapse contamination in photometric samples of Type Ia Supernovae

This is an exciting time for cosmology with type Ia supernovae (SNe Ia). The recentlyconcluded Dark Energy Survey SN programme (DES-SN) has obtained the largest anddeepest high-redshift cosmological SN Ia sample, and the Vera Rubin Observatory isexpected to observe at least one order of magnitude more SNe Ia in the next decade.In both these experiments, only a limited fraction (.10 per cent) of the SNe can bespectroscopically classified. This leaves us with large ‘photometric’ SN samples, withthe potential for significant contamination by core-collapse SNe that may bias SN Iacosmological measurements. This thesis demonstrates how this contamination can bemodelled and accounted for in current and future cosmological analyses.First, I present state-of-the-art simulations of the SN universe. These are designedto accurately model the population of SNe Ia, peculiar SNe Ia and core-collapse SNe, aswell as their host galaxies. To improve the diversity and quality of the simulated corecollapseSNe, I build a new library of core-collapse SN templates using spectroscopicand photometric (optical and near-ultraviolet) data of 67 core-collapse SNe from theliterature. I account for our incomplete knowledge of core-collapse SN properties bygenerating a set of SN simulations (rather than a single one), each exploring differentmodelling choices and template libraries. I then characterise selection effects in theDES-SN survey and incorporate them in the simulations, thus obtaining a series ofDES-like simulated SN samples that can be compared to the observed DES-SN data.The agreement between the simulations and data is excellent across many observed SNproperties, including Hubble residuals. These simulations are the first to reproduce theobserved photometric SN and host galaxy properties in high-redshift surveys with no fine-tuning of the input parameters.I use my simulation framework to train and test the performance of SuperNNova,a photometric SN classifier based on recurrent neural networks. I explore differenttraining and validation strategies and show that, across all the DES-SN simulationstested, SuperNNova reduces core-collapse SN contamination to 0.8–3.5 per cent. Ithen show that biases due to contamination on the equation-of-state of dark energy,w, are < 0:008 when using our reference SuperNNova model. This compares to anexpected statistical uncertainty on w from the DES-SN sample of 0:039, thus showing that contamination is not a limiting systematic for the cosmological analysis of theDES-SN sample.The results presented in this thesis are the foundation of the DES SN Ia cosmologicalanalysis; they also provide important implications for the future of SN cosmology,as they demonstrate that contamination is not expected to significantly degrade thecosmological figure of merit of the Rubin SN Ia analysis.

79 ASTRONOMY AND ASTROPHYSICS↗

Embedding condition describing shearing, dissipative collapse

Highlights: • Perturbative approach to the time-dependent Karmarkar condition in shearing collapse. • Analysis of the (in)stability of the collapsing fluid using the TOV equation. • Study of the temperature profiles using a causal heat transport equation. In this work we employ the time-dependent Karmarkar condition to model dissipative gravitational collapse in the presence of shear which leads to a final static configuration. We believe that this is a first attempt at using the time-dependent Karmarkar condition describing a radiating star with shear in which the collapsing core dissipates energy in the form of a radial heat flux. The final static configuration which is described by an embedding class I spacetime was obtained by Hansraj and Moodly who showed that this solution satisfies all the physical requirements for a static compact object. As the collapse proceeds and the heat flux tends to zero the dynamical core evolves into a static compact core with the exterior spacetime being described by the vacuum Schwarzschild solution.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Storage-Induced Collapse of Lignin Macromolecular Structure and Its Impacts on the Biorefinery

Lignin plays a vital role in the economics of biorefineries, serving as a source of process energy and a feedstock for sustainable fuels and chemical production. While understanding lignin’s chemical composition is crucial, emerging evidence suggests that a more comprehensive understanding of its macromolecular structure is critical to explaining its complex behavior in the biorefinery. This study investigated the partial collapse of the lignin network in corn stover feedstock after harvest and storage as a result of the microbial digestion of hemicellulose. Fluorescence microscopy was used to detect the collapse of lignin in terms of lignin’s inter-molecular interaction and the re-orientation of lignin’s chromophores, by the changes in lignin’s fluorescence lifetime, anisotropy, and the number of effective emitters. With minimal sample perturbation, our in-situ microscopic results revealed lignin's coil-globule transition phenomena, which was only previously predicted by molecular dynamics modeling extracted lignin in solvent. This collapse of lignin macromolecular structure was confirmed by results from NMR, IR, Raman, and powder X-ray diffraction. We also investigated the impact of this storage-induced collapse on the downstream biorefinery processes. Our study revealed that the two major approaches for lignin valorization in the lignin-first biorefinery model, namely monomer extraction and milled wood lignin extraction, were negatively impacted by the lignin collapse. As changes during storage are a source of feedstock variability, our study highlights the importance of understanding the effect of feedstock handling on biorefinery operations and economics.

09 BIOMASS FUELS↗

Dynamics of an inertially collapsing gas bubble between two parallel, rigid walls

The collapse of cavitation bubbles in channel flows can give rise to structural damage along neighbouring walls. Although the collapse of a bubble near a single wall has been studied extensively, less is known about bubble collapse between two walls, e.g. as in a channel. We conduct highly resolved, direct simulations of the Navier–Stokes equations to investigate the bubble dynamics and pressures produced by the collapse of a bubble between two parallel rigid walls. We examine the dependence of the dynamics and pressures on the initial bubble location, confinement and driving pressure. For a fixed initial stand-off distance, as the channel width increases the bubble volume, migration distance and re-entrant jet speed approach their single-wall counterparts. We obtain an expression for the minimum channel width at which the confinement does not affect the bubble dynamics depending on the driving pressure difference and initial stand-off distance. For a fixed channel width, varying stand-off distance reduced the maximum wall pressures in the channel relative to the single wall; the trend was consistent for three different driving pressures. Two different jetting behaviours are seen when the bubble is centred in the channel, depending on the channel width. Under significant confinement, wall-parallel re-entrant jets impinge upon each other and further intensify the collapse of the vortex ring.

Rodriguez, Jr, Mauro (ORCID:0000000305450265)↗

Accurately simulating core-collapse self-interacting dark matter halos

The properties of satellite halos provide a promising probe for dark matter (DM) physics. Observations have motivated current efforts to explain surprisingly compact DM halos. If DM is not collisionless, but has strong self-interactions, halos can undergo gravothermal collapse, leading to higher densities in the central region of the halo. However, it is challenging to model this collapse phase from first principles. To improve on this, we sought to better understand the numerical challenges and convergence properties of self-interacting dark matter (SIDM) N-body simulations in the collapse phase. Especially, our aim was to better understand the evolution of satellite halos. To do so, we ran SIDM N-body simulations of a low-mass halo in isolation and within an external gravitational potential. The simulation set-up was motivated by the perturber of the stellar stream GD-1. We find that the halo evolution is very sensitive to energy conservation errors, and a SIDM kernel size that is too large can artificially speed up the collapse. Moreover, we demonstrate that the King model can describe the density profile at small radii for the late stages that we have simulated. Furthermore, for our most highly resolved simulation (N = 5 × 10 7 ) we have made the data public. It can serve as a benchmark. Overall, we find that the current numerical methods do not suffer from convergence problems in the late collapse phase and provide guidance on how to choose numerical parameters, for example that the energy conservation error is better kept well below 1%. This allows simulations to be run of halos that become concentrated enough to explain observations of GD-1-like stellar streams or strong gravitational lensing systems.

dark matter↗

Sudden collapse of a pressure profile generated by off-axis heating in a linear magnetized plasma

Here, the features of an unexpected, large event that arises spontaneously during a basic heat transport experiment are presented. It consists of the sudden collapse of the radial plasma pressure profile, akin to disruption events observed in toroidal magnetic confinement devices. The experiment is performed on the Large Plasma Device at the University of California, Los Angeles (UCLA). It uses a LaB6 thermionic emitter of annular shape to induce off-axis heating of a cold, afterglow plasma, in a linear magnetic geometry. The temporal evolution consists of three regimes. During an early, quiescent period, classical heat transport along and across the magnetic field arises from Coulomb collisions. After significant pressure gradients develop, drift-Alfvén waves become unstable. Upon reaching large amplitude, they trigger avalanche events that flatten the outer part of the heated region, which, in turn, quenches the instability. Due to the sustained heating, the pressure profile rebuilds and the process repeats, leading to a relatively long, second regime that displays multiple avalanches, but suddenly, the annular pressure profile is observed to collapse. After this collapse, the system enters a third regime with large fluctuations. Before the collapse, a rapid, runaway heating environment arises whose time evolution exhibits a self-similar dependence on the applied voltage. The time evolution, morphology, and scaling of the collapse event are presented, and an examination is made of the underlying mechanisms.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Mechanics of pore array collapse and interaction in shock-compressed polymethyl methacrylate (PMMA)

Recent studies on dynamic pore collapse have revealed significant development of shear localization, which can lead to material failure in porous structures and hot spot generation in energetic materials. These findings have dramatically improved the understanding of failure mechanisms during pore collapse but also prompt further investigation of realistic porous materials. In particular, porous media consist of many pores and porous networks. Even in low-porosity materials, pores can form in close proximity during the manufacturing process, leading to the critical question of pore–pore interaction during collapse under dynamic loading conditions. This study investigates, via plate impact experiments coupled with high-speed internal digital image correlation and shadowgraphy techniques, the collapse of two pores in shock-compressed PMMA at stresses between 0.4 and 1 GPa. The results of these experiments provide new insights into shear localization in pore collapse, in addition to distinct interactions between pores. Shadowgraphy measurements reveal novel, direct visualization of shear band development and crack evolution from pore surfaces. Spacing between adiabatic shear bands is measured over a range of impact stresses and is predicted accurately by the Grady–Kipp model. Pore interactions are found to effect a transition in the impact stress threshold at which different failure mechanisms initiate and are also found to possibly influence preferential sites for shear cracking. Throughout the study, numerical and theoretical models are leveraged to understand shear localization behavior. The role of baroclinicity and wave interactions between the pores is used to elucidate interaction mechanisms between pores.

Lawlor, Barry P. [California Institute of Technolo↗

Numerical challenges in modeling gravothermal collapse in Self-Interacting Dark Matter halos

When dark matter has a large cross section for self scattering, halos can undergo a process known as gravothermal core collapse, where the inner core rapidly increases in density and temperature. To date, several methods have been used to implement Self-Interacting Dark Matter (SIDM) in N-body codes, but there has been no systematic study of these different methods or their accuracy in the core-collapse phase. In this paper, we compare three different numerical implementations of SIDM, including the standard methods from the GIZMO and Arepo codes, by simulating idealized dwarf halos undergoing significant dark matter self interactions (σ/m = 50 cm 2 /g). When simulating these halos, we also vary the mass resolution, time-stepping criteria, and gravitational force-softening scheme. The various SIDM methods lead to distinct differences in a halo's evolution during the core-collapse phase, as each results in spurious scattering rate differences and energy gains/losses. The use of adaptive force softening for gravity can lead to numerical heating that artificially accelerates core collapse, while an insufficiently small simulation time step can cause core evolution to stall or completely reverse. Additionally, particle numbers must be large enough to ensure that the simulated halos are not sensitive to noise in the initial conditions. Even for the highest-resolution simulations tested in this study (10 6 particles per halo), we find that variations of order 10% in collapse time are still present. Here, the results of this work underscore the sensitivity of SIDM modeling on the choice of numerical implementation and motivate a careful study of how these results generalize to halos in a cosmological context.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Moment tensor event identification for collapses

SUMMARY We introduce a seismic identification method for collapse events using moment tensors (MTs). We start by computing full (six-element) MT solutions for 43 identified collapse events from around the world, and statistically characterizing the population on the MT hypersphere. We then test a large data set of over 1000 full MTs for the western U.S. against the distribution of collapses using a MT-based identification method similarly as used for testing explosions. Known collapses and explosions are readily identified, along with other anomalous events in the Geysers and central California coast. Misidentification rates are determined for various screening angles with optimal misidentification rates between earthquakes and collapses on the order of 3 per cent. The method is demonstrated to be very effective at identifying non-earthquake sources with a 97–98 per cent accuracy. It is likely to be transportable to other regions, and can be used for event identification anywhere full MT solutions are routinely calculated.

58 GEOSCIENCES↗

Axion structure formation – II. The wrath of collapse

ABSTRACT The first paper in this series showed that quantum chromodynamic axion dark matter, as a highly correlated Bose fluid, contains extra-classical physics on cosmological scales. The source of the derived extra-classical physics is exchange–correlation interactions induced by the constraints of symmetric particle exchange and interaxion correlations from self-gravitation. The paper also showed that the impact of extra-classical physics on early structure formation is marginal, as the exchange–correlation interaction is inherently non-linear. This paper continues the study of axion structure formation into the non-linear regime, considering the case of full collapse and virialization. The N-body method is chosen to study the collapse, and its algorithms are derived for a condensed Bose fluid. Simulations of isolated gravitational collapse are performed for both Bose and cold dark matter fluids using a prototype N-body code. Unique Bose structures are found to survive even the most violent collapses. Bose post-collapse features include dynamical changes to global structures, creation of new broad sub-structures, violations of classical binding energy conditions, and new fine structures. Effective models of the novel structures are constructed and possibilities for their observation are discussed.

79 ASTRONOMY AND ASTROPHYSICS↗

Collapse of neutrino wave functions under Penrose gravitational reduction

Models of spontaneous wave function collapse have been postulated to address the measurement problem in quantum mechanics. Their primary function is to convert coherent quantum superpositions into incoherent ones, with the result that macroscopic objects cannot be placed into widely separated superpositions for observably prolonged times. Many of these processes will also lead to loss of coherence in neutrino oscillations, producing observable signatures in the flavor profile of neutrinos at long travel distances. The majority of studies of neutrino oscillation coherence to date have focused on variants of the continuous state localization model, whereby an effective decoherence strength parameter is used to model the rate of coherence loss with an assumed energy dependence. Another class of collapse models that have been proposed posit connections to the configuration of gravitational field accompanying the mass distribution associated with each wave function that is in the superposition. A particularly interesting and prescriptive model is Penrose’s description of gravitational collapse which proposes a decoherence time τ determined through E g τ ∼ ℏ , where E g is a calculable function of the Newtonian gravitational potential. Here we explore application of the Penrose collapse model to neutrino oscillations, reinterpreting previous experimental limits on neutrino decoherence in terms of this model. We identify effects associated with both spatial collapse and momentum diffusion, finding that the latter is ruled out in data from the IceCube South Pole Neutrino Observatory so long as the neutrino wave packet width at production is σ ν , x ≤ 2 × 10 − 12 m . Published by the American Physical Society 2024

Astronomy & Astrophysics↗

Strontium-84 Enrichments in Presolar Grains Provide First Evidence of p -process Nucleosynthesis in Core-collapse Supernovae

This study reports detection of rare p-process isotopes within presolar grains. Presolar grains are relic dust grains from dying stars. These microscopic dust particles are found in primitive solar system materials. Their distinct isotopic compositions record the nucleosynthetic processes in their parent stars and the Galactic chemical environment in which these stars formed. We studied presolar graphite grains of high-density type from the Murchison meteorite and found five grains with subgrains that show enrichments in 84 Sr compared to the solar abundance. 84 Sr is the neutron-deficient isotope of strontium that can be produced in the deep oxygen-rich interior of high-mass stars that end their lives as core-collapse supernovae. The observed 84 Sr excesses cannot be produced in low-mass asymptotic giant branch stars, the source of most high-density presolar graphites found in meteorites. High-density graphites with embedded 84 Sr excesses are, instead, compatible with a core-collapse supernovae origin. The graphite subgrains condensed from carbon-rich materials in the outer layers of core-collapse supernovae, where 84 Sr was destroyed by neutron captures during hydrostatic evolution of the stars and their final explosion. Based on current theoretical stellar models, a few percent of contribution from the inner regions of core-collapse supernovae, which are enriched in p-process nuclides, to the outer carbon-rich regions is the most likely explanation for the observed enrichment of 84 Sr in the subgrains of the high-density graphites. In this study, we present the first observational evidence that core-collapse supernovae produce and eject isotopes made by the p-process.

Astronomy and AstroPhysics↗

Door assembly with collapsible carrier

A door assembly for a motor vehicle comprised of an outer door panel and an inner door panel interconnected to define a door panel structure having an internal door cavity. A collapsible carrier module is configured to be oriented in a collapsed arrangement to facilitate installation into the door cavity through an opening in the inner door panel. The collapsible carrier module can be moved from its collapsed arrangement into an expanded arrangement upon installation within the door cavity to facilitate subsequent mounting to the door panel structure. The collapsible carrier module includes a two-piece carrier plate formed to integrally include a pair of laterally-spaced glass run channels and a pair of laterally-spaced slider rails.

42 ENGINEERING↗

Door assembly with collapsible carrier and water shield

A door assembly for a motor vehicle comprised of an outer door panel and an inner door panel interconnected to define a door panel structure having an internal door cavity. A collapsible carrier module is configured to be oriented in a collapsed arrangement to facilitate installation into the door cavity through an opening in the inner door panel. The collapsible carrier module can be moved from its collapsed arrangement into an expanded arrangement upon installation within the door cavity to facilitate subsequent mounting to the door panel structure. The collapsible carrier module includes a barrier configured to close off the opening in the inner panel.

Fortin, Raymond Edward↗

Data-scarce surrogate modeling of shock-induced pore collapse process

Understanding the mechanisms of shock-induced pore collapse is of great interest in various disciplines in sciences and engineering, including materials science, biological sciences, and geophysics. However, numerical modeling of the complex pore collapse processes can be costly. To this end, a strong need exists to develop surrogate models for generating economic predictions of pore collapse processes. Here, in this work, we study the use of a data-driven reduced-order model, namely dynamic mode decomposition, and a deep generative model, namely conditional generative adversarial networks, to resemble the numerical simulations of the pore collapse process at representative training shock pressures. Since the simulations are expensive, the training data are scarce, which makes training an accurate surrogate model challenging. To overcome the difficulties posed by the complex physics phenomena, we make several crucial treatments to the plain original form of the methods to increase the capability of approximating and predicting the dynamics. In particular, physics information is used as indicators or conditional inputs to guide the prediction. In realizing these methods, the training of each dynamic mode composition model takes only around 30 s on CPU. In contrast, training a generative adversarial network model takes 8 h on GPU. Moreover, using dynamic mode decomposition, the final-time relative error is around 0.3% in the reproductive cases. We also demonstrate the predictive power of the methods at unseen testing shock pressures, where the error ranges from 1.3 to 5% in the interpolatory cases and 8 to 9% in extrapolatory cases.

97 MATHEMATICS AND COMPUTING↗