Collapse Model Research Articles

Analytic models for gravitational collapse

Analytic models for gravitational collapse

Quantitative efficiency of optoacoustic ultrasonic treatment in SLM, DED, and LBW applications

Ultrasound can improve the quality of finished products by reducing porosity and enhancing microstructure in selective laser melting, directed energy deposition, and laser beam welding. This study evaluates the efficiency of ultrasound produced by a pulsed laser via the optoacoustic effect. A quantitative model of collapse of vapor-gas bubbles has been developed under the conditions of ultrasonic treatment at near resonance frequencies. Based on the simulation results, the phenomenological expressions are suggested to determine the optimal operating frequency and power for the pulsed laser to alter the microstructure and porosity effectively via cavitation. The analysis is performed for the 316 L stainless steel and titanium Ti-6Al-4 V alloy, which are common in additive manufacturing.

Impact of the shape of the prestellar density fluctuations on the core mass function

Abstract It is well known that departure from sphericity in the geometry of primordial dark matter halos modifies their mass function. The ellipsoidal collapse model yields a better agreement with simulations of hierarchical clustering than the original, spherical model. In the present paper, we examine the same issue in the context of star formation by studying the impact of non-sphericity of density perturbations in a gravoturbulent medium on the prestellar core mass function (CMF). An important question, notably, is to find out how ellipsoidal, instead of spherical, initial density fluctuations modify both the high-mass and low-mass tails of the CMF. Our study shows that triaxial density fluctuations indeed depart from a purely spherical form but the deformation (prolateness and ellipticity) remains modest, suggesting that the usual hypothesis of spherical collapse in existing theories of the IMF is reasonable. We find that, as in the cosmological case, the departure from sphericity increases the collapse barrier, stabilizing the prestellar cores. The striking difference between the stellar case and the cosmological one for the ellipsoidal collapse model is that, although in both cases the less dense structures are the most deformed, they correspond to small scales, thus low mass halos in cosmology but to large scales, thus large mass cores in star formation. As a result, the high mass range of the CMF is the most affected by the ellipsoidal collapse, resulting in a slightly less steep slope than the one predicted with the spherical hypothesis and a peak slightly shifted toward lower masses.

Additive Manufacturing of Personalized Brain-Computer Interface Headsets Reinforced by Scientific Visualization

Recently, a large attention has been attracted to the brain-computer human-machine interfaces (BCI) based on electroencephalography (EEG). This emerging technology allows touchless control over digital systems, in which the commands are based on human brain activity. In the ideal case, it means controlling the systems virtually by thoughts, but in reality, also simpler approaches are highly demanded like reacting to concentration, relaxation, or specific emotions. Modern BCIs are based on detecting so-called brain waves, the electromagnetic field oscillations induced by brain neurons. These waves are captured by electrodes either intruded into the brain or placed on top of the head. Obviously, placing electrodes on the head is more demanded for non-medical applications of BCI because it is absolutely harmless for the person. To achieve this, special headsets are needed which can be put on the head like a helmet and ensure the correct positions for the electrodes mounted on them. In this regard, wearing comfort and anatomical accuracy of headsets play an important role in ensuring both ergonomics and precision of BCI. This paper focuses on automation of the personalized EEG headset manufacturing for BCI. The technological chain is proposed and corresponding software tools are developed to foster the complete cycle of BCI headset production for a particular person. The production steps include 3D scanning of the head, interactive editing of the electrodes’ location system, and automatic generation of a collapsible head cap model with sockets for EEG electrodes optimized for 3D printing. The performance of the pipeline has been validated in practice. The accuracy of electrodes’ placement has been evaluated by comparison with the head cap from professional medical equipment and is established as sufficient for BCI. The headset model editing and customizing tools are powered with scientific visualization and cognitive graphics techniques to be friendly for a wide range of users including those with no dedicated IT skills.

Influence of the C + H2O -> H2CO solid-state reaction onastrochemical networks and the formation of complex organic molecules

The solid-state reaction C + H$_2$O rightarrow H$_2$CO has recently been studied experimentally and claimed as a new `non-energetic' pathway to complex organic and prebiotic molecules in cold astrophysical environments. We compared results of astrochemical network modelling with and without the C + H$_2$O surface reaction. A typical, generic collapse model in which a dense core forms from initially diffuse conditions was used along with the astrochemical kinetics model MAGICKAL. The inclusion of the reaction does not notably enhance the abundance of formaldehyde itself; however, it significantly enhances the abundance of methanol (formed by the hydrogenation of formaldehyde) on the dust grains at early times, when the high gas-phase abundance of atomic C leads to relatively rapid adsorption onto the grain surfaces. As a result, the gas-phase abundance of methanol is also increased due to chemical desorption, quickly reaching abundances close to sim 10$^ $ n$_H$, which decline strongly under late-time, high-density conditions. The reaction also influences the abundances of simple ice species, with the CO$_2$ abundance increased in the earliest, deepest ice layers, while the water-ice abundance is somewhat depressed. The abundances of various complex organic molecules are also affected, with some species becoming more abundant and others less. When gas-phase atomic carbon becomes depleted, the grain-surface chemistry returns to behaviour that would be expected if there had been no new reaction. Our results show that fundamental reactions involving the simplest atomic and molecular species can be of great importance for the evolution of astrochemical reaction networks, thus providing motivation for future experimental and theoretical studies.

Simulation of a Potential Sector Collapse on the Koryaksky Volcano and Volcanic Hazard Assessment for the Yelizovo-Petropavlovsk Agglomeration (Kamchatka)

Based on the modeling of a potential sector collapse on the Koryaksky volcano, the most probable direction of movement of a debris avalanche is shown. Periodic fumarole activity of the volcano indicates the circulation of meteoric waters and favorable conditions for the replacement of the volcano bedrock with the development of landslide deposits. On the basis of satellite data, deformations of the earth's surface have been studied. The northeastern slopes of Koryaksky volcano rise relative to the descending southwestern slopes. Taking into account the fact that Avachinsky volcano, which is located 10 km from the Koryaksky volcano, has formed powerful landslide-explosive deposits in the history of its development, the relevance of this study is extremely high. Within the Yelizovo-Petropavlovsk agglomeration (which includes the cities of Yelizovo, Petropavlovsk-Kamchatsky and the adjacent settlements of the Yelizovsky district), which is located in the immediate vicinity of the Koryaksky volcano, more than half of the total population of the Kamchatka region lives and there are enterprises that bring more than half of all financial profit of the region. Therefore, the assessment of hazardous natural processes on the Koryaksky volcano in order to further develop a plan to minimize their negative consequences is critical for the economy of Kamchatka.

Verification of Adhesive Forces Reduction By Surface Modification Treatment in Finfet Patterns: A Molecular Dynamics Simulation Study

Since the pattern collapse was reported for the first time it has been getting more critical issue in wet cleaning process along with semiconductor scaling. The model of the pattern collapse is that structures such as fins deform due to capillary force during drying step, then they contact and stick each other due to surface tension. One technique to prevent pattern collapse involves lowering the surface tension by modifying the surface’s silanol groups with functional groups[1]. The expected mechanism is that the adhesive force becomes smaller than the elastic force of the pattern due to the reduced surface tension. However, the details, including the dynamics, are still unclear. In particular, how functional groups affect fin contact from a molecular perspective remains unknown. Clarifying these issues is crucial because it will lead to a better understanding of the pattern collapse, subsequently enhancing semiconductor fabrication efficiency. Molecular dynamics (MD) simulation is a useful tool to elucidate these phenomena, as it can obtain physical properties and forces of the system from statistical thermodynamics and visualize nanoscale dynamics[2].In this study, we prepared models of fins modified with trimethyl silanol (TMS) and calculated the adhesive forces between them by using MD techniques. We utilized the MD solver Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS) and the visualizer Open Visualization Tool (OVITO) [3, 4].The fin model utilized in these calculations is depicted in Figure 1. The size of the simulation box was 15.360×2.304×42.000 nm. Periodic boundary conditions were applied in the x and y directions, while specular boundary condition was applied in the z direction. This model primarily consisted of Si atoms. The height of fins was 30 nm, with the top 10 nm terminated by OH groups (912 in total) and the remaining terminated by H atoms. Here we introduced TMS substitutions for randomly selected OH groups. The numbers of substitutions were 0, 91, 228, and 365, resulting in 0%, 10%, 25%, and 40% TMS models, respectively. To reduce bias arising from the random placement of TMS groups, five TMS models were created for each level of TMS substitution. The first step in the calculation process involved placing water between the fins to simulate a wet condition and induce pattern collapse, followed by conducting a 2.0 ns MD calculation. As a result, in every model, the fins came into contact each other (Figure 1b). Subsequently, all water molecules were removed to simulate a dried condition, followed by a 2.0 ns MD calculation. In all models, under the dry condition, the fin contact established during the wet condition was kept (Figure 1c, d). The average adhesive forces between 1.0 ns and 2.0 ns of the MD trajectory after water removal were analyzed, revealing that the forces in the 10%, 25%, and 40% TMS models were less than 1/3 of those in the 0% TMS models. We interpret that, despite the persistence of pattern collapse in the dry condition, restoring the initially separated fins appears more feasible in TMS-modified surface models. The details will be reported in an oral presentation.[1] T. Koide et al., "Effect of Surface Energy Reduction for Nano-Structure Stiction," ECS Transactions, vol. 69, no. 8, p. 131, 2015, doi: 10.1149/06908.0131ecst.[2] R. Seki et al., "Insights into FinFET Structure Collapse: A Reactive Force Field-Based Molecular Dynamics Investigation," Solid State Phenomena, vol. 346, p. 123, 2023, doi: 10.4028/p-mUO0Oa.[3] A. P. Thompson et al., "LAMMPS - a flexible simulation tool for particle-based materials modeling at the atomic, meso, and continuum scales," Computer Physics Communications, vol. 271, p. 108171, 2022, doi: 10.1016/j.cpc.2021.108171.[4] A. Stukowski, "Visualization and analysis of atomistic simulation data with OVITO–the Open Visualization Tool," Modelling and Simulation in Materials Science and Engineering, vol. 18, no. 1, p. 015012, 2010, doi: 10.1088/0965-0393/18/1/015012.Figure 1: (a) The wet Fin model with inter-fin water molecules for MD simulations. The top 10 nm of the fins were terminated with OH groups, while the remaining were terminated with H atoms. Through the introduction of TMS substitutions for randomly selected OH groups, we prepared 10%, 25%, and 40% TMS models. (b) The snapshot of MD simulation after 2.0 ns from the initial configuration of (a). (c) The dry model prepared by removing water molecules from the configuration of (b). (d) The snapshot of MD simulation after 2.0 ns from the configuration of (c). Figure 1

Testing continuous spontaneous localization model with charged macromolecules

Abstract In the last decade, a growing interest has been devoted to models of spontaneous collapse of the wavefunction, known also as collapse models. They coherently solve the well-known quantum measurement problem by suitably modifying the Schrödinger evolution. Quantum experiments are now finally within the reach of testing such models (and thus testing the limits of quantum theory). Here, we propose a method based on a two-ions confined in a linear Paul trap to possibly enhance the testing capabilities of such experiments. The combination of an atomic and a macromolecular ion provide a good match for the cooling of the motional degrees of freedom and a non-negligible insight in the collapse mechanism, respectively.

Unveiling the prediction model and mechanism of the collapse of bank slope in the lancangjiang area

This study takes the bank collapse at the left bank of Badi Township of the Lidi Hydropower Station in the Lancang Area as an example. To address the lack of in-depth research on the prediction model and mechanisms of bank collapse, this study conducts field drilling surveys, investigates influencing factors, analyzes causal mechanisms, and proposes prediction methods based on the geological survey data of bank collapse in the reservoir area. The study explores the stratigraphic lithology, determines the key parameters for bank collapse prediction, and studies the failure modes and bank collapse mechanisms. It also proposes the finite element method of bank collapse to predict the width and elevation of bank collapse and provides the influence on the surrounding environment. The results show that the collapsed bank on the left bank of Badi Township is a high and steep soil-like slope, and forms the collapse and retreat type of failure mode after impoundment. The Kachukin method, the bank slope structure method, and the proposed finite element method are used to predict the width and elevation of the collapsed bank. The results indicate that the Kachujin method predicts a larger range of bank collapses and is biased towards safety. In contrast, the prediction ranges of the bank slope structure method and the finite element method are close. The bank collapse position is located in the middle and rear of the residential houses in Badi Township, which is consistent with the on-site investigation and has strong reliability. The predicted width of the bank collapse is about 34 m and the elevation is about 1,845 m. The research results can be directly applied to preventing and controlling bank collapse and have powerful practical application value.

Model Test on Acoustic Emission Monitoring of Loess Slope Failure.

The three stages of loess collapse are characterized by notable concealment and sudden onset due to the sudden nature of loess collapse and the prolonged duration of the peristaltic deformation stage. Traditional displacement monitoring methods struggle to detect early signals of instability and failure, leading to poor timeliness in disaster warnings. This project begins by examining non-force field information related to the loess collapse process. It focuses on acoustic emission monitoring and employs model tests to identify effective waveguide rods for monitoring loess collapse. Additionally, the project investigates the evolution anomalies of acoustic emission parameters before and after loess collapse failure, aiming to establish early warning criteria for loess collapse based on acoustic emission. This work provides a theoretical basis for monitoring and early warning of loess collapses. This study evaluates five parameters of the active waveguide system: sensor installation method, filling material, waveguide rod wall thickness, outer wrapping material, and outer wrapping wall thickness. The densities of the filler materials were tested using the optimal parameters derived from the tests to identify the best configurations for active acoustic emission (AE) waveguide systems suitable for monitoring loess collapse. Subsequently, a one-sided connected loess collapse model was employed for indoor tests, integrating real-time AE monitoring with the active waveguide method. This model facilitates the exploration of AE response characteristics during loess collapse and the analysis of destructive forms of loess collapse and time-sequence evolution of AE ringing counts throughout the deformation and destruction process. Results indicate that using filler materials with high elasticity modulus, high compactness, and low Poisson's ratio, along with thin outer wrapping and waveguide rod walls, leads to strong AE signals. As deformation damage of loess collapse intensifies, the number of AE ringing counts notably increases. A rapid rise in cumulative ringing counts can indicate a "sudden increase", or the b-value may stabilize, providing precursor information for loess collapse.

Decoding Quantum Gravity Information with Black Hole Accretion Disk

Integrating loop quantum gravity with classical gravitational collapse models offers an effective solution to the black hole singularity problem and predicts the formation of a white hole in the later stages of collapse. Furthermore, the quantum extension of Kruskal spacetime indicates that white holes may convey information about earlier companion black holes. Photons emitted from the accretion disks of these companion black holes enter the black hole, traverse the highly quantum region, and then re-emerge from white holes in our universe. This process enables us to observe images of the companion black holes’ accretion disks, providing insights into quantum gravity. In our study, we successfully obtained these accretion disk images. Our results indicate that these accretion disk images are confined within a circle with a radius equal to the critical impact parameter, while traditional accretion disk images are typically located outside this circle. As the observational angle increases, the accretion disk images transition from a ring shape to a shell-like shape. Furthermore, the positional and width characteristics of these accretion disk images are opposite to those of traditional accretion disk images. These findings provide valuable references for astronomical observations aimed at validating the investigated quantum gravity model.

Signatures of Mass Segregation from Competitive Accretion and Monolithic Collapse

The two main competing theories proposed to explain the formation of massive (>10 M ⊙) stars—competitive accretion and monolithic core collapse—make different observable predictions for the environment of the massive stars during, and immediately after, their formation. Proponents of competitive accretion have long predicted that the most massive stars should have a different spatial distribution to lower-mass stars, through the stars being either mass segregated or being in areas of higher relative densities or sitting deeper in gravitational potential wells. We test these predictions by analyzing a suite of smoothed-particle hydrodynamics simulations where star clusters form massive stars via competitive accretion with and without feedback. We find that the most massive stars have higher relative densities, and sit in deeper potential wells, only in simulations in which feedback is not present. When feedback is included, only half of the simulations have the massive stars residing in deeper potential wells, and there are no other distinguishing signals in their spatial distributions. Intriguingly, in our simple models for monolithic core collapse, the massive stars may also end up in deeper potential wells because if massive cores fragment then the stars that form are also massive, and dominate their local environs. We find no robust diagnostic test in the spatial distributions of massive stars that can distinguish their formation mechanisms, and so other predictions for distinguishing between competitive accretion and monolithic collapse are required.

The Origin of Magnetofossil Coercivity Components: Constraints From Coupled Experimental Observations and Micromagnetic Calculations

AbstractBiogenic magnetite crystals produced by magnetotactic bacteria (MTB) and associated magnetofossils in sediments are characterized by variable morphologies, grain sizes, and chain structures. Magnetofossils are widely used in paleomagnetic and paleoenvironmental studies, but the complex magnetofossil shapes and particle arrangements significantly affect magnetic properties, hampering their magnetic detection and proxy interpretation. Here we perform coupled experimental and micromagnetic modeling analyses of typical magnetofossil‐rich sediments, where the effects of magnetofossil crystal forms and microstructures on magnetic properties can be quantitatively separated. Since the in situ magnetofossil chain structures in sediments remain poorly known, we compare results from magnetic measurements and micromagnetic simulations based on realistic magnetofossil shapes and grain size distributions. Our results suggest that bullet‐shaped magnetofossils certainly contribute to the biogenic hard (BH) coercivity component with a minor contribution from elongated prismatic particles, and collapsed equidimensional grains to the biogenic soft (BS) component. Micromagnetic simulations with different collapse models of bullet‐shaped magnetofossils produce variable FORC (first‐order reversal curve) central‐ridge contributions with similar coercivity distributions. Sensitivity test suggests that samples containing different forms of magnetofossils can produce the BH coercivity component if the proportion of the bullet‐shaped particles is more than ∼2%. Magnetofossil assemblages with a higher proportion of bullet‐shaped particles have higher coercivities, squareness ratios, and larger BH contents. Our data shed new light on understanding the origin of magnetofossil coercivity components and the in situ magnetofossil microstructures in sediments, which is widely useful for interpreting magnetofossil proxy signals in geological records.

Impact of ice growth on the physical and chemical properties of dense cloud cores

We investigated the effect of time-dependent ice growth on dust grains on the opacity and hence on the dust temperature in a collapsing molecular cloud core, with the aim of quantifying the effect of the dust temperature variations on ice abundances as well as the evolution of the collapse. To perform the simulations, we employed a one-dimensional collapse model that self-consistently and time-dependently combines hydrodynamics with chemical and radiative transfer simulations. The dust opacity was updated on the fly based on the ice growth as a function of the location in the core. The results of the fully dynamical model were compared against simulations run with different values of fixed ice thickness. We found that the ice thickness increases quickly and reaches a saturation value (as a result of a balance between adsorption and desorption) of approximately 90 monolayers in the central core (volume density ~104 cm−3), and several tens of monolayers at a volume density of ~103 cm−3, after only a few 105 yr of evolution. The results thus exclude the adoption of thin (approximately ten monolayer) ices in molecular cloud simulations except at very short timescales. However, the differences in abundances and the dust temperature between the fully dynamic simulation and those with a fixed dust opacity are small; abundances change between the solutions generally within a factor of two only. The assumptions on the dust opacity do have an effect on the collapse dynamics through the influence of the photoelectric effect on the gas temperature, and the simulations take a different time to reach a common central density. This effect is, however, small as well. In conclusion, carrying out chemical simulations using a dust temperature corresponding to a fixed opacity seems to be a good approximation. Still, although at least in the present case its effect on the overall results is limited – as long as the grains are monodisperse – ice growth should be considered to obtain the most accurate representation of the collapse dynamics. We have found in a previous work that considering a grain size distribution leads to a complicated ice composition that depends on the grain size nonlinearly. With this in mind, we will carry out a follow-up study where the influence of the grain size on the present simulation setup is investigated.

Mass scaling relations for dark halos from an analytic universal outer density profile

Context. The average matter density within the turnaround scale, which demarcates where galaxies shift from clustering around a structure to joining the expansion of the Universe, is an important cosmological probe. However, a measurement of the mass enclosed by the turnaround radius is difficult. Analyses of the turnaround scale in simulated galaxy clusters place the turnaround radius at about three times the virial radius in a ΛCDM universe and at a (present-day) density contrast with the background matter density of the Universe of δ ~ 11. Assessing the mass at such extended distances from a cluster’s center is a challenge for current mass measurement techniques. Consequently, there is a need to develop and validate new mass-scaling relations, to connect observable masses at cluster interiors with masses at greater distances. Aims. Our research aims to establish an analytical framework for the most probable mass profile of galaxy clusters, leading to novel mass scaling relations, allowing us to estimate masses at larger scales. We derive such analytical mass profiles and compare them with those from cosmological simulations. Methods. We used excursion set theory, which provides a statistical framework for the density and local environment of dark matter halos, and complement it with the spherical collapse model to follow the non-linear growth of these halos. Results. The profile we developed analytically showed good agreement (better than 30%, and dependent on halo mass) with the mass profiles of simulated galaxy clusters. Mass scaling relations were obtained from the analytical profile with offset better than 15% from the simulated ones. This level of precision highlights the potential of our model for probing structure formation dynamics at the outskirts of galaxy clusters.

Large scale massively parallel numerical simulation for blast effects on structures

An efficient large-scale parallel computing program for blast effects on structures is developed based on software platform mode, which adopts component-based three-layer software architecture to achieve disciplinary hierarchy. The parallel layer encapsulates high-performance data structures and shields large-scale parallel computing technology, enabling efficient mesh adaptivity. The common numerical algorithm layer encapsulates fluid, structural, and coupling algorithm processes providing standardized interfaces for extending numerical schemes. The physical model layer provides extension interfaces for state equations, source terms, initial boundary values, etc, to facilitate quick customization of large-scale parallel software for blast effects on structures. Typical examples verify the correctness, effectiveness and high precision of the proposed program in fluid-structure coupling problems. The parallel efficiency of 300,000 processor cores with hundreds of millions of grids reach 60.84% for the shock wave transmission. Finally, the dynamic behavior of multi-storey buildings under blast waves is simulated to reveal the damage model of the overall collapse. These results show that the software has a broad application prospect in the field of explosion. The results suggest that the software holds significant potential for application in the field of explosion, particularly in intricate and large-scale scenarios.

Magnetohydrodynamical modeling of star-disk formation: from isolated spherical collapse towards incorporation of external dynamics

The formation of protostars and their disks has been understood as the result of the gravitational collapse phase of an accumulation of dense gas that determines the mass reservoir of the star-disk system. Against this background, the broadly applied scenario of considering the formation of disks has been to model the collapse of a dense core assuming spherical symmetry. Our understanding of the formation of star-disk systems is currently undergoing a reformation though. The picture evolves from interpreting disks as the sole outcome of the collapse of an isolated prestellar core to a more dynamic picture where disks are affected by the molecular cloud environment in which they form. In this review, we provide a status report of the state-of-the-art of spherical collapse models that are highly advanced in terms of the incorporated physics together with constraints from models that account for the possibility of infall onto star-disk systems in simplified test setups, as well as in multi-scale simulations that cover a dynamical range from the Giant Molecular Cloud environment down to the disk. Considering the observational constraints that favor a more dynamical picture of star formation, we finally discuss the challenges and prospects in linking the efforts of tackle the problem of star-disk formation in combined multi-scale, multi-physics simulations.

Construction and validation of clinical prediction model of tongue base collapse under drug-induced sleep endoscopy in OSA patients

Objective: To analyze the correlation between drug-induced sleep endoscopy (DISE), results, polysomnography (PSG) indicators, and clinical parameters in patients with obstructive sleep apnea (OSA), and to establish and validate a predictive model for tongue base plane obstruction. Methods: This retrospective study analyzed 117 OSA patients diagnosed via PSG and treated at the Department of Otolaryngology-Head and Neck Surgery, Nanfang Hospital, Southern Medical University, between October 2014 and March 2022. The cohort comprised of 114 males and 3 females, with an age range of 20 to 54 years (mean age 38.1±8.4 years). Data on DISE results, PSG results, and clinical indicators were collected for all 117 patients. Logistic regression analysis was performed to identify relevant indicators, and a predictive model for tongue base plane obstruction was constructed and internally validated using the R programming language. Results: Univariate logistic regression analysis identified four independent risk factors for predicting tongue root plane obstruction: tonsil grading, N2, N3, and rapid eye movement sleep(REM) stage [OR:0.412(0.260~0.652),1.045(1.012~1.079),0.943(0.903~0.984),0.961(0.925~0.998),P <0.05]. Multivariate logistic regression analysis confirmed tonsil grading and N3 sleep stage (12.48±12.22%) as significant predictors. A nomogram model incorporating these factors demonstrated good predictive performance, with an area under curve(AUC) of 0.82 (95%CI: 0.548-1.000), an optimal cutoff of 0.519, a specificity of 80.0%, and a sensitivity of 86.7%. Internal validation of the model in the validation cohort yielded an AUC of 0.751 (95%CI: 0.625-0.876). Conclusions: Tongue base plane obstruction observed during DISE in OSA patients is associated with tonsil grading and N3 sleep stage duration. The predictive model developed for tongue base plane obstruction based on DISE demonstrates good efficacy, as evidenced by its internal validation.

Large-Deformation Modeling of Surface Instability and Ground Collapse during Tunnel Excavation by Material Point Method

Recent rapid urbanization has led to an increase in tunnel construction, escalating the prevalence of ground collapses. Ground collapses, characterized by large deformation and strain-softening, pose a significant challenge for classical numerical theories and simulation methods. Consequently, a numerical framework combining the material point method (MPM) and strain-softening Drucker–Prager plasticity is introduced in this study to more accurately describe the evolution process and failure mechanism of the subgrade during tunnel excavation. The proposed numerical framework was validated against an analytic solution employing a typical ‘dry bottom’ dam model with solid non-linearity and large deformation; some of the results are also compared with those of the SPH method and centrifugal modeling tests to verify the validity of the MPM method in this paper. The validated model was used in this study to conduct a comprehensive analysis of surface instability and ground collapse under varying soil conditions. This included factors such as strata thickness, cohesion, internal friction angle, and a quantitative description of the development of longitudinal subsidence of the surface. The aim was to clarify deformation responses, failure patterns, and excavation mechanisms, providing insights for underground tunneling practices.

Collapse of the Dharahara Tower During the April 25, 2015 Nepal Earthquake: A New Interpretation Based on Video-Camera Footage

ABSTRACT Among the various important monuments impacted by the April 25, 2015 Mw7.8 Nepal earthquake, the Dharahara Tower located in Kathmandu suffered complete collapse. The collapse of the tower, a slender 60-meter-high old brick masonry structure with an almost cylindrical hollow shape, was captured by a low-quality video camera, which nonetheless helped to identify the critical moments. Initially, the tower descended more than 10 m vertically after a rupture at the base. After a few seconds, it overturned, disintegrating upon impact on the ground. At a distance of 1.3 km, an accelerometric station recorded the strong motion which was used as input of a discrete element model of the structure. Mechanical properties were taken from lab tests made on similar building materials. The Dharahara Tower had previously been analysed by other researchers using various methods. However, since they were apparently not aware of the mechanism observed in the video footage, their collapse models do not agree with this new evidence. For the initial phase of the collapse, the present model explains with great accuracy the observations of the video footage, but the final phase is dependent on various details, and modelling is not so robust.