Detailed Numerical Simulations Research Articles

Simulating electromagnetic cascades with Lorentz invariance violation

Lorentz invariance violation (LIV) is a phenomenon featuring in various quantum gravity models whereby Lorentz symmetry is broken at high energies, potentially impacting the behaviour of particles and their interactions. Here we investigate the phenomenology of LIV within the context of gamma-ray–induced electromagnetic cascades. We conduct detailed numerical simulations to explore the expected manifestations of LIV on gamma-ray fluxes, taking into account relevant effects such as pair production and inverse Compton scattering. Additionally, we consider processes forbidden in the standard model, namely vacuum Cherenkov emission and photon decay. Our analysis reveals that these modifications result in distinct characteristics within the measured particle fluxes at Earth, which have the potential to be observed in high-energy gamma-ray observations.

Frequency diversity of modal dispersion in mode-division multiplexing systems from strong to weak coupling regimes

Based on a statistical model applicable to all mode-coupling regimes and a trace covariance function of the group-delay matrix for characterizing the modal-dispersion correlation, we study the frequency diversity of modal dispersion in randomly-perturbed mode-division multiplexing optical communication systems. Particularly, we conduct detailed numerical simulation and analysis on the statistical properties of the modal dispersion in a 6-mode fiber under random perturbation. The results show that, at two frequencies of sufficiently large difference, while the modal dispersion eventually gets uncorrelated in the strong coupling regime, there remains a significant amount of “residual” correlation in the weak coupling regime. Also, we find that, although the typically-assumed frequency-domain ergodicity is reasonably valid in the strong coupling regime, it clearly fails in the weak coupling regime. The crossover from the strong to weak coupling regimes is also quantitatively investigated.

Effects of joint invasion: How co-invaders affect each other's success in model food webs?

While there has been considerable research on the interactions between invasive and native species, and on the impact of invasive species on the resident community, there has been less focus on exploring the relationship and interactions among invasive species themselves. Nevertheless, it is widely recognised that invasive species can have either positive or negative effects on each other, as well as neutral outcomes. In the present theoretical study, we compared the success of two invasive non-native species in two scenarios: when they invaded the resident food web separately and simultaneously. We examined the correlations between their direct and indirect ecological relationships and their topological positions in the food web, with the varying outcomes of joint invasion. Using the Allometric Bioenergetic Model (ABM) for dynamic simulations, we determined the success of invasion (presence or absence of invaders) and, in the case of successful co-invasion, the direction of their biomass change, comparing separate and simultaneous invasion scenarios. We studied the relationships between these variables after detailed numerical simulations with variable key parameters of the model.We found that direct and indirect ecological relationships between the two invaders can significantly modifiy the outcomes of the invasion scenarios. For example, their predator-prey relationship increases the probability of invasion success for both invaders, but at the same time the equilibrium biomass of at least one of them is likely to be reduced compared to its separate invasion. Trophic cascade or competitive relationship between them during simultaneous invasion also affects their success rate, with the former having a positive effect and the latter a negative one, as they can hinder each other's spread. Further, we found that higher trophic level and lower betweenness centralities of the invaders reduces the likelihood of invasion success regardless of the presence or absence of another invasive species. The results of the study can be tested experimentally in micro- and mesocosms.

Numerical vibrational acoustics and sound quality assessment of pipa strings

This study harmonizes subjective auditory and psychological elements related to plucked strings with objective physical attributes through spectrum analysis and numerical simulation, confirming the congruity between objective assessment systems and subjective perceptions in evaluating pipa string sound quality. The research combines experimental investigation of plucked pipa string vibrations with detailed numerical simulations of vibrational acoustic fields using a specified 3 N input force. Results demonstrate that as frequency increases (from A4: 440 Hz to E6: 1320 Hz), more pronounced vibrations emerge along the pipa body, leading to heightened overall sound pressure within the vibrational acoustic fields. The sound pressure distribution analysis reveals that the rosewood pipa exhibits significantly lower standard deviations of 41.8% and 41.9% compared to the tung wood pipa, and 24.6% and 32.2% lower than the white wood pipa at 440 Hz and 1320 Hz, respectively, highlighting the rosewood pipa’s superior sound pressure uniformity. Additionally, an assessment of the A4 signal’s Power Spectral Density (PSD) distribution underscores even spectral energy dispersion in the rosewood pipa’s A4 sound signal, with minor resonance peaks in higher-order overtones beyond 5000 Hz, further substantiating the superior sound quality of the rosewood pipa, in line with expert reviews.

Practical approaches for evaluating radiative heat from high pressure hydrogen flame

As the construction of hydrogen stations and other hydrogen-related facilities progresses, it becomes increasingly crucial for safety designs to account for scenarios where leaked hydrogen might ignite. Since a hydrogen flame is usually invisible, detection must rely on radiative heat or temperature. While it is possible to predict accurate radiative heat flux from a high pressure hydrogen jet flame through detailed numerical calculations of hydrogen combustion with its radiation, the objective of this study is to provide a simpler and more accurate prediction method. Previous experimental data of radiative heat flux, Qr from high pressure hydrogen jet flames were compiled, and a simple experimental equation Qr=1463.3(Lo/Lf)−2.32 was derived, where Lf and Lo represent the flame length and the distance perpendicular to the flame axis from the midpoint of the flame length to the observer, respectively. Radiative heat fluxes were computed through detailed numerical simulations using three types of water vapor radiation models: Goody's narrow random band model, the exponential broad band model by Edward and Elsasser's narrow regular band model. The temperature and water vapor partial pressure distributions obtained from numerical simulations were used as input conditions. The results were found to be in good agreement with the experimental equation. Moreover, a simple diagram representing the radiative heat flux from a hydrogen flame was derived using the method of cylinder-like approximation. The results of this study show that if the hydrogen pressure and leakage aperture diameter are given, the radiative heat flux at a certain distance can be predicted with high accuracy. Additionally, the average value of emissivity for the hydrogen diffusion flame was found to be on the order of 0.03.

End-to-end simulations of exoplanet detection with multiplexed volume Bragg gratings

Direct imaging of exoplanets greatly enhances our ability to spectroscopically detect molecules in their atmospheres, but requires both excellent angular and spectral resolution. A highly promising approach uses multiplexed transmission gratings to achieve compressed sensing, but the published theoretical calculations are not realistic enough to determine whether the approach is feasible. We aim to determine the performance of recovering exoplanet signals of an instrument with multiplexed volume Bragg gratings in a full, detailed numerical simulation, specifically examining any effects caused by multiplexing several gratings. Our end-to-end simulation includes realistic stellar and planetary spectra, a closed-loop adaptive optics simulation, and rigorous coupled wave analysis to model the multiplexed gratings. We chose 20 passbands around expected methane absorption features that were optically combined using 20 gratings. We find that exoplanet signals can be recovered down to contrasts of $10^ $, without the addition of a coronagraph. Multiplexing a larger number of gratings improves the deepest recovered contrast, if photon noise is the dominant noise source. When residuals from our simple post-processing approach are the largest noise source, a larger number of multiplexed gratings decreases the performance, due to the stacking of the PSFs at different wavelengths. This is an artifact of our data reduction approach. We conclude that multiplexed Bragg gratings are a viable method to look for exoplanets with a compressed sensing approach and additional gains may be made in post-processing.

Automatic Detection of Nuclear Spins at Arbitrary Magnetic Fields via Signal-to-Image AI Model.

Quantum sensors leverage matter's quantum properties to enable measurements with unprecedented spatial and spectral resolution. Among these sensors, those utilizing nitrogen-vacancy (NV) centers in diamond offer the distinct advantage of operating at room temperature. Nevertheless, signals received from NV centers are often complex, making interpretation challenging. This is especially relevant in low magnetic field scenarios, where standard approximations for modeling the system fail. Additionally, NV signals feature a prominent noise component. In this Letter, we present a signal-to-image deep learning model capable of automatically inferring the number of nuclear spins surrounding a NV sensor and the hyperfine couplings between the sensor and the nuclear spins. Our model is trained to operate effectively across various magnetic field scenarios, requires no prior knowledge of the involved nuclei, and is designed to handle noisy signals, leading to fast characterization of nuclear environments in real experimental conditions. With detailed numerical simulations, we test the performance of our model in scenarios involving varying numbers of nuclei, achieving an average error of less than 2kHz in the estimated hyperfine constants.

Modelling the adverse impacts of urbanization on human health

Abstract Urbanization has been a growing trend for decades, but the Coronavirus disease 2019 (COVID-19) pandemic has accelerated this trend in several ways. In many countries, the pandemic has prompted significant investments in urban health infrastructure, including hospitals, clinics, and public health facilities. Also, there are many studies suggesting that COVID-19, urbanization, and chronic diseases are interconnected in several ways, and addressing one aspect requires a comprehensive approach that considers the interconnectedness of these factors. To date, there are no studies depicting COVID-19 as a cause of emerging chronic diseases within the urban population. To address this sensitive issue, we propose a mathematical model in which we divide the total human population into three compartments: susceptible, diseased, and recovered. We have obtained the equilibrium points of the model and the conditions for their local stabilities. A suitable Lyapunov function has been used to derive the condition for the global stability of the nontrivial equilibrium point. A detailed numerical simulation of the model has been carried out, which is followed by sensitivity analysis of the model system.

Direct Evidence of Klein and Anti-Klein Tunneling of Graphitic Electrons in a Corbino Geometry.

Transport measurement of electron optics in monolayer graphene p-n junction devices has been traditionally studied with negative refraction and chiral transmission experiments in Hall bar magnetic focusing setups. We show direct signatures of Klein (monolayer) and anti-Klein (bilayer) tunneling with a circular "edgeless" Corbino geometry made out of gated graphene p-n junctions. Noticeable in particular is the appearance of angular sweet spots (Brewster angles) in the magnetoconductance data of bilayer graphene, which minimizes head-on transmission, contrary to conventional Fresnel optics or monolayer graphene which show instead a sharpened collimation of transmission paths. The local maxima on the bilayer magnetoconductance plots migrate to higher fields with increasing doping density. These experimental results are in good agreement with detailed numerical simulations and analytical predictions.

Anomalous Pressure Diffusion and Deformation in Two‐ and Three‐Dimensional Heterogeneous Fractured Media

AbstractIn fractured and stress‐sensitive reservoirs and aquifers, hydromechanical coupling is important, in connection with their heat and solute transport properties, and because the fluid production or extraction leads to land subsidence and potentially to induced seismicity. Classical dual‐porosity poroelasticity (DPP) models cannot upscale pressure diffusion and deformation in fractured porous media, which are characterized by anomalous behaviors that manifest in strong tailing in the temporal evolution of flow rate and subsidence. We study these behaviors using detailed numerical simulations of fluid production in naturally fractured formations characterized by multi‐Gaussian distributions of the matrix permeability. We find that the tailing behaviors depend on the permeability contrast between fracture and matrix, on the permeability distribution in the matrix, and on the correlation length. We use a non–equilibrium, multi‐porosity model to quantify the coupled behaviors of anomalous pressure diffusion, fluid flow and deformation. The model is parameterized by medium and fluid properties, which set the characteristic pressure diffusion time scales. It allows to identify the emerging scaling regimes and scaling behaviors of flow rate and subsidence. We propose a model implementation that captures the full anomalous evolution of flow rates and displacements observed in the detailed numerical simulations in terms of the permeability distribution and matrix length scales. The presented results shed new light on the controls of medium heterogeneity and geometry on pressure diffusion, fluid production and subsidence in highly heterogeneous fractured media.

Hydrodynamic force and torque models for cylindrical particles in a wide range of aspect ratios

During the pneumatic conveyance of biomass in a coal-fired power station boiler, biomass particles have cylindrical shapes with different aspect ratios. They move through the fluid at any angle and rotate strongly. However, highly accurate and general models of the drag, lift, and torque coefficients (CD, CL, and CT) for biomass particles in a wide range of aspect ratios, especially the CT model and the high aspect ratios, are currently lacking. This paper presents detailed direct numerical simulations of the flow around cylindrical cylinders with varying aspect ratios (6 ≤ AR ≤ 22), Reynolds numbers (100 ≤ Re ≤ 2000), and angles of incidence (0° ≤ θ ≤ 90°). The simulation was conducted using the OpenFOAM solver with the body-fitted mesh method. The flow characteristics and force coefficients of cylindrical particles with different AR were systematically analyzed. New functional correlations between CD, CL, and CT and AR, Re, and θ values were established. The mean squared errors for CD, CL, and CT were 8.8 × 10–2, 2.4 × 10–2, and 4.7 × 10–2, with average relative errors of 5.8%, 3.5%, and 8.17%, respectively. A comparison of the results with other experimental and simulation data in previous literatures showed that the new CD and CL models have considerable higher predictive ability. The generality of the new CD model expanding to low ARs of 1.5 and 3 is verified finally. The new force and torque models are expected to improve the accuracy of Eulerian–Lagrangian simulations of various cylindrical particle-laden flows in the utility of biomass energy.

Compensating thermal bending of the runner disk in hydrodynamic thrust bearings: Simple approach for passively improving the performance of gas bearings

This paper presents a method for passively compensating thermal bending distortions of the thrust disk in gas thrust bearings by passive approaches. Thermal bending displays a prominent problem in hydrodynamic thrust bearings, especially in connection with air bearings. Axial temperature gradients cause the rotor disk to dish which in turn diminishes the lubricating gap topology and reduces the load capacity of the bearing. Consequently, the bearing performance is decreased and the bearing may even fail. The here proposed straightforward solutions are small changes in the rotor and runner disk design and are therefore rather simple and inexpensive to adopt. They comprise asymmetric mass distributions, recesses, disk cuts, and dual-material rotor disks. In order to show the benefit for the thrust bearing performance, detailed multiphysical numerical simulations of a representative rotor assembly with a foil thrust bearing are presented. The fully coupled finite element model calculates the deformations of the foil package (2D Reissner–Mindlin type shell equations), lubricating air film pressure (2D compressible Reynolds equation), air film temperatures (3D energy equation), and thermo-elastic deformations of the rotor and rotor disk (2D Navier-Lamé equations including centrifugal forces and thermal stresses). When the proposed design changes are applied, the model predicts reduced thermal bending, marked improvements in load capacity as well as decreased temperatures. The load capacity increase ranges up to 43% for an optimized design when compared against a standard symmetric design. Also, the sensitivity of different design parameters is discussed in detail. The suggested disk design changes may be applied to a broad variety of rotor-bearing systems. However, the design has to be tailored to the specific and individual machine operating conditions.

Nonlinear spreading behavior across multi-platform social media universe.

Understanding how harmful content (mis/disinformation, hate, etc.) manages to spread among online communities within and across social media platforms represents an urgent societal challenge. We develop a non-linear dynamical model for such viral spreading, which accounts for the fact that online communities dynamically interconnect across multiple social media platforms. Our mean-field theory (Effective Medium Theory) compares well to detailed numerical simulations and provides a specific analytic condition for the onset of outbreaks (i.e., system-wide spreading). Even if the infection rate is significantly lower than the recovery rate, it predicts system-wide spreading if online communities create links between them at high rates and the loss of such links (e.g., due to moderator pressure) is low. Policymakers should, therefore, account for these multi-community dynamics when shaping policies against system-wide spreading.

Formula omitted]symmetric tight-binding 1D chains: Coupling to the continuum and superradiance transition

By the use of the transfer matrix (TM) approach and effective non-Hermitian Hamiltonian (EnHH) approach we study transport and scattering properties of PT−symmetric tight-binding one-dimensional (1D) chains. In the TM approach we derive an exact expression for the transmission T through 1D chains that incorporates all the scattering-system parameters: incident-wave energy E, chain length L, gain/loss amplitude γ, and coupling strength to perfect leads χ. We show that the behavior of T vs. L strongly depends on the value of γ with respect to the critical value γcr, defined through γcr2=4−E2. For γ<γcr, the transmission T is a periodic function of L, however, for γ>γcr, T decreases exponentially with L. We also predict the unforeseen dependence T∝L−2 at γ=γcr. By the use of the EnHH approach to the same model which is now connected to continuum through left and write ends, we focus on the onset of the superradiance transition as a function of E, L, γ, and χ. The main interest here is in the competition between the balanced gain/loss terms in the bulk of the chain and the coupling to continuum through the ends of the chain. Our results demonstrate that the presence of the gain/loss in the bulk strongly modifies the width of non-superradiant states, however, did not change the width of the superradiant ones. The analytical predictions are supported by detailed numerical simulations.

The minimum mass for star formation by dynamical fragmentation: dependence on epoch, dust abundance, and environment

ABSTRACT We estimate the minimum mass of a star formed by dynamical collapse and fragmentation, as a function of epoch, dust abundance, and environment. Epoch is parametrized by redshift, zred, through the variation in the temperature of the cosmic microwave background. The dust abundance is parametrized by the mass-fraction in dust, ZD, with the additional simplifying assumption that the intrinsic properties of dust do not change with ZD, only the amount of dust. Environment is parametrized by the energy-density of the ambient suprathermal radiation fields through a dilution factor ω⋆ (applied to a blackbody radiation field at $T_{\star }=10^4\, {\rm K}$). The critical condition is that a spherical proto-fragment should be able to cool, and therefore contract, fast enough to detach from neighbouring proto-fragments. The minimum mass increases with increasing redshift, increasing dust abundance, and increasing suprathermal background. Values in the range from $M_{{\rm MIN}}\sim 0.002\, {\rm M}_{\odot }$ to $M_{{\rm MIN}}\sim 0.2\, {\rm M}_{\odot }$ are obtained at the extremes of the parameter ranges we have considered (0 ≤ zred ≤ 8, 0.00016 &amp;lt; ZD &amp;lt; 0.04, and 10−15 ≤ ω⋆ ≤ 10−8). Our results agree quite well with the predictions of detailed numerical simulations invoking similar redshifts and dust abundances, but our estimates are somewhat lower; we attribute this difference to resolution issues and the small-number statistics from the simulations. The increased minimum masses predicted at high redshift and/or high suprathermal background result in significantly bottom-light initial mass functions, and therefore low mass-to-light ratios, provided that the dust abundance is not too low. The changes due to high suprathermal background may be particularly important for star formation in galactic nuclei and at high redshift.

Study on the Influence of Deep Soil Liquefaction on the Seismic Response of Subway Stations

Subway systems are a crucial component of urban public transportation, especially in terms of safety during seismic events. Soil liquefaction triggered by earthquakes is one of the key factors that can lead to underground structural damage. This study investigates the impact of deep soil liquefaction on the response of subway station structures during seismic activity, aiming to provide evidence and suggestions for earthquake-resistant measures in underground constructions. The advanced finite element software PLAXIS was utilized for dynamic numerical simulations. Non-linear dynamic analysis methods were employed to construct models of subway stations and the surrounding soil layers, including soil–structure interactions. The UBC3D-PLM liquefaction constitutive model was applied to describe the liquefaction behavior of soil layers, while the HS constitutive model was used to depict the dynamic characteristics of non-liquefied soil layers. The study examined the influence of deep soil liquefaction on the dynamic response of subway station structures under different seismic waves. The findings indicate that deep soil liquefaction significantly increases the vertical displacement and acceleration responses of subway stations compared to non-liquefied conditions. The liquefaction behavior of deep soil layers leads to increased horizontal effective stress on both sides of the structure, thereby increasing the horizontal deformation of the structure and posing a potential threat to the safety and functionality of subway stations. This research employed detailed numerical simulation methods, incorporating the non-linear characteristics of deep soil layer liquefaction, providing an analytical framework based on regulatory standards for evaluating the impact of deep soil liquefaction on the seismic responses of subway stations. Compared to traditional studies, this paper significantly enhances simulation precision and practical applicability. Results from this research indicate that deep soil layer liquefaction poses a non-negligible risk to the structural safety of subway stations during earthquakes. Therefore, the issue of deep soil liquefaction should receive increased attention in engineering design and construction, with effective prevention and mitigation measures being implemented.

Numerical simulation of the 2010 4-story reinforced concrete structure tested on the E-defense shake table

Due to advancements in computational tools, performing a full nonlinear response history analysis of structures at the system level using detailed numerical simulations of components has become less demanding, even on standard personal computers. However, the modelling approaches need to be calibrated and verified against experimental measurements to ensure the accuracy of the system-level predictions. In this study, an advanced numerical simulation method is used to predict the 3D nonlinear dynamic response of a four-story reinforced concrete building tested at E-Defense shake table. The structure is modelled in the finite element analysis programme DIANA, using a previously developed and validated approach to predict the failure modes of doubly reinforced walls with confined boundary regions. Curved shell elements are used to model the walls and slabs, and the reinforcement is modelled using embedded bar elements. The frame elements are modelled using beam elements with the effect of confinement on the concrete behaviour represented in the material constitutive model. The numerical versus experimental response comparison is conducted at both local and global levels. For local levels, the base shear versus top displacement curves, strain gradients as well as the crack pattern predicted by the numerical model are compared with the test measurements. The inter-story drift response history is considered as the metric for the global level assessment. The effects of different modelling parameters on the accuracy of predictions are also investigated.

A unified exponential-H family for modeling real-life data: Properties and inference

The exponential distribution is one of the most widely used statistical distribution for reliability issues. In this paper, we introduce a novel family based on the exponential model, called the new exponential-H (NEx-H) family. The sub-models of the NEx-H family are capable of accommodating variable failure rates, as well as unimodal, bimodal, left-skewed, symmetric, right-skewed, and J-shape densities. The mathematical features of the NEx-H family are derived. The parameters of the NEx-Weibull distribution are estimated by using seven estimation methods. Detailed numerical simulations are presented. Based on our study, the maximum likelihood is the best estimation method for estimating the NEx-Weibull parameters. Three real-life data sets are fitted using the NEx-Weibull distribution. The NEx-Weibull model provides better fit as compared to some competing Weibull models.

Tungsten Inert Gas Welding of 6061-T6 Aluminum Alloy Frame: Finite Element Simulation and Experiment.

In order to address the irregularity of the welding path in aluminum alloy frame joints, this study conducted a numerical simulation of free-path welding. It focuses on the application of the TIG (tungsten inert gas) welding process in aluminum alloy welding, specifically at the intersecting line nodes of welded bicycle frames. The welding simulation was performed on a 6061-T6 aluminum alloy frame. Using a custom heat source subroutine written in Fortran language and integrated into the ABAQUS environment, a detailed numerical simulation study was conducted. The distribution of key fields during the welding process, such as temperature, equivalent stress, and post-weld deformation, were carefully analyzed. Building upon this analysis, the thin-walled TIG welding process was optimized using the response surface method, resulting in the identification of the best welding parameters: a welding current of 240 A, a welding voltage of 20 V, and a welding speed of 11 mm/s. These optimal parameters were successfully implemented in actual welding production, yielding excellent welding results in terms of forming quality. Through experimentation, it was confirmed that the welded parts were completely formed under the optimized process parameters and met the required product standards. Consequently, this research provides valuable theoretical and technical guidance for aluminum alloy bicycle frame welding.

Multi-objective genetic algorithm calibration of colored self-compacting concrete using DEM: an integrated parallel approach.

A detailed numerical simulation of Colored Self-Compacting Concrete (CSCC) was conducted in this research. Emphasis was placed on an innovative calibration methodology tailored for ten unique CSCC mix designs. Through the incorporation of multi-objective optimization, MATLAB's Genetic Algorithm (GA) was seamlessly integrated with PFC3D, a prominent Discrete Element Modeling (DEM) software package. This integration facilitates the exchange of micro-parameter values, where MATLAB's GA optimizes these parameters, which are then input into PFC3D to simulate the behavior of CSCC mix designs. The calibration process is fully automated through a MATLAB script, complemented by a fish script in PFC, allowing for an efficient and precise calibration mechanism that automatically terminates based on predefined criteria. Central to this approach is the Uniaxial Compressive Strength (UCS) test, which forms the foundation of the calibration process. A distinguishing aspect of this study was the incorporation of pigment effects, reflecting the cohesive behavior of cementitious components, into the micro-parameters influencing the cohesion coefficient within DEM. This innovative approach ensured significant alignment between simulations and observed macro properties, as evidenced by fitness values consistently exceeding 0.94. This investigation not only expanded the understanding of CSCC dynamics but also contributed significantly to the discourse on advanced concrete simulation methodologies, underscoring the importance of multi-objective optimization in such studies.