Physical Model Research Articles

Quantifying the High Early Solar Cosmic-Ray Flux with Cosmogenic Neon Isotopes in Refractory Minerals

An enhancement in the activity of the early young Sun resulting in a high charged particle flux has been invoked to explain excesses in spallation-induced nuclides in primitive planetary materials. Astronomical observations of energetic outbursts of young stellar objects (YSOs) also support the idea of an active young Sun. However, the early solar cosmic-ray (SCR) flux has not been well constrained. Here we use measured concentrations of SCR-produced nuclides that formed and are preserved in meteoritical hibonite and spinel, some of the solar system’s oldest solids, and physical models for dust transport in the early protoplanetary disk to determine the magnitude of the early SCR flux. We focus our attention on cosmogenic neon, which cannot have been inherited from precursors and can only be produced in situ in solids. Our modeled effective exposure time to SCRs for these solids is very short, on the order of years. This indicates that the young Sun’s SCR flux recorded in refractory mineral hibonite was up to ∼7 orders of magnitude higher than the contemporary level. Our flux estimate is consistent with the >105× enhanced flux inferred from astronomical observations of greatly enhanced flare activities of YSOs.

Pressure Distributions in Glottal Geometries With Multichannel Airflows

Computer simulation of self-sustained oscillation of the vocal folds has been successful with application of simple Bernoulli-like driving pressures. As voice simulation is now applied to asymmetric vibration with complex mode structures that yield partial vocal fold contact, the driving pressures need refinement. Two independent approaches were used to obtain pressure distributions. The first was a high-fidelity immersed-boundary method computation and the second was a series of pressure tap measurements on scaled-up physical models. Glottal geometries were based on normal surface modes of vibration. Samples are chosen from a large inventory of measured and calculated profiles. Pressure distributions show the complexity that can exist in the driving forces on vocal fold surfaces. Qualitative similarity between computation and measurement was established for a variety of contact patterns, showing diverse pressure gradients in multiple directions. Simplified Bernoulli approaches to glottal pressure distributions are defensible when a single flow channel is preserved in vocal fold oscillation. However, when there are contact islands that produce confluence or difluence of multiple airflow channels, the pressure gradients vary profoundly. Small quantitative differences were observed between measurement and calculation, primarily due to spatial sampling.

ThunderBoltz: an open-source direct simulation Monte Carlo Boltzmann solver for plasma transport, chemical kinetics, and 0D modeling

Abstract Plasma-neutral interactions, including reactive kinetics, are often either studied in 0D using ODE-based descriptions, or in multi-dimensional fluid or particle-based plasma codes. The latter case involves a complex assembly of procedures that are not always necessary to test effects of underlying physical models and mechanisms for particle-based descriptions. Here we present ThunderBoltz, a lightweight, publicly available 0D direct simulation Monte Carlo code designed to accommodate a generalized combination of species and arbitrary cross sections without the overhead of expensive field solves. It can produce electron, ion, and neutral velocity distributions in applied AC/DC E-field and/or static B-field scenarios. The code is built in the C++ standard library and includes a convenient Python interface that allows for input file generation (including compatibility with cross section data from the LXCat database), electron transport and reaction rate constant post-processing, input parameter constraint satisfaction, calculation scheduling, and diagnostic plotting. These codes can be accessed at the repository: https://github.com/lanl/ThunderBoltz. In this work we compare ThunderBoltz transport calculations against Bolsig+ calculations, benchmark test problems, and swarm experiment data, finding good agreement with all three in the appropriate field regimes. In addition, we present example use cases where the electron, ion, and background neutral particle species are self-consistently evolved to model the background kinetics, a feature that is absent in fixed-background Monte Carlo and n-term Boltzmann solvers. The latter functionality allows for the possibility of particle-based chemical kinetics simulations of the plasma and neutral species as a new alternative to ODE-based approaches.

Preliminary Verification of Key Physical Models in Oxide Fuel Performance Analysis Code FEATURE Based on COMSOL

Nuclear performance analysis is of great significance for fuel design optimization and the safe operation of a reactor. Considering the design requirements of the China initiative Accelerator Driven System (CiADS) project, it is necessary to develop relevant fuel performance analysis tools to predict fuel performance evolution during service. The Fuel Element Analysis Tool for Undercritical Reactor Engineering (FEATURE) code, based on the advanced multiphysics coupling platform COMSOL software, is under development in this context, with a current focus on oxide fuel for fast reactors. This paper mainly conducts preliminary comparative verification of the oxygen redistribution, plutonium redistribution, and fission gas release modules of the FEATURE code through model examples, code-to-code evaluation, and experimental data. The results indicate that the FEATURE code exhibits good accuracy and reliability in simulating oxygen and plutonium redistribution, as well as fission gas release, making it suitable for integrated coupling calculations.

How attentive is a student in class? A concentration evaluation method based on head Euler angle

How attentive is a student in class? It is an interesting and challenging question in the field of education research. In this paper, a concentration evaluation method based on head Euler angle is proposed. First, a fine large-small-interval video sampling strategy is advocated and concepts of dynamic threshold and action amplitude coefficient are defined, which are fused together to get the head up rate. Second, head front-facing rate is computed through analyzing the yaw angle, which is obtained from a proposed spatial physical model of camera and student seat position. Third, for any given time period, class concentration of a student is derived by fusing and normalizing the head up rate and head front-facing rate based on Euclidean-distance. Finally, accuracy experiments are conducted, where the proposed method achieves an average accuracy of 89.8% compared with the average score from the questionnaire given by 22 reviewers. Also, robust experiments on several head pose estimation models are facilitated, which achieves an average accuracy of 98.43% on recorded video dataset, indicates insensitivity to the head pose estimation model used for data collection and verifies that the proposed method is independent on any specific head pose estimation model. The experimental results show that the proposed method is accurate, effective and robust for the concentration evaluation in class.

Innovative Method for Fixed-Bed Physical Model Construction Applying Modern Materials and Techniques

Innovative Method for Fixed-Bed Physical Model Construction Applying Modern Materials and Techniques

An investigation on hydrodynamic behavior of horizontal gas–liquid intermittent flow by S-PLIF and parallel-wire conductance sensors

Horizontal gas–liquid two-phase flows widely exist in a variety of industrial fields such as the environment, chemical industry and energy. Intermittent flow, characterized by the quasi-periodic alternation motion of liquid slugs and large-scale Taylor bubbles, is the most prevalent flow pattern in horizontal gas–liquid two-phase flows. Comprehensive research on the hydrodynamic behavior of gas–liquid intermittent flow is essential for revealing the mass and heat transfer characteristics between phases, thereby establishing physical models of flow parameters. In this study, a structured planar laser-induced fluorescence (S-PLIF) system and paired parallel-wire conductance sensors (PWCSs) are designed to detect the gas–liquid interface structures and the hydrodynamic parameters. The S-PLIF system consists of a laser, a visualization box, a Ronchi ruling-plate and a pair of high-speed cameras. An optical linear prism forms a laser sheet in the transverse direction and the middle of the test section, and the cameras are positioned at 70° and 90° respectively to the plane of the laser sheet, referred to as S-PLIF70 and S-PLIF90. Under the laser excitation, bright and dark stripes generated by the Ronchi ruling-plate are deflected at the gas–liquid interface. The influence of total reflection can be effectively avoided by identifying the deflection position of the stripes, allowing for accurate detection of the gas–liquid interfacial structures. The effects of the interface fluctuations and detached bubbles on the S-PLIF70&90 results are investigated. Fluctuation and evolution characteristics of the gas–liquid interface are analyzed by probability density function (PDF) and power spectral density (PSD). Meanwhile, hydrodynamic parameters, i.e., Taylor bubble nose and tail velocity, Taylor bubble and slug length, and slug frequency, are detected by the PWCSs, and compared with previous correlations. The evolution characteristics of the interfacial structures and hydrodynamic parameters are uncovered as the flow condition changes.

Physical Model of Landslide‐Generated Impulse Waves: Experimental Investigation of the Wave‐Granular Flow Coupling

AbstractLarge amplitude and unexpected waves are a regular source of natural disasters. Among them, impulse waves generated by landslides can represent a significant threat. Therefore, predicting and measuring the generation of such waves is essential. In this study, the phenomenon is modeled by a 2D‐experimental setup using a steady non‐uniform granular flow along a slope as a forcing wave generator. The present device provides a continuous supply of grains to avoid finite volume effects, as the part of the landslide actually involved in the wave generation strongly depends on the configuration and is not necessarily available in geophysical events. This system consists of an energy transfer between the granular flow and the wave generation which is characterized by a Froude number. It is found that the latter cannot be defined only based on the dry flow properties to characterize the wave. In particular, the dynamics underwater influence wave generation during a finite time. Accordingly, the present study shows that the wave maximum amplitude is governed by a newly defined Froude number, based on both dry and underwater granular flow properties. Moreover, it is shown that the granular deposit, specifically its runout, can be thought as a proxy of the immersed granular dynamics as long as the impact properties are still considered.

Deriving measurement collapse using zeta function regularisation and speculative measurement theory

This paper shows how an application of zeta function regularisation to a physical model of quantum measurement yields a solution to the problem of wavefunction collapse. Realistic measurement dynamics based on a particle becoming non-isolated are introduced and, based on this, an outcome function is derived using the method of maximum entropy. It is shown how regularisation of an information theoretic quantity related to this outcome function leads to apparent collapse of the wavefunction. The physical principles and key assumptions that underlie this theory are discussed. Some possible experimental approaches are described.

Evaluating hydrological responses of satellite precipitation products over an Indian tropical catchment through a distributed physical model

AbstractSignificant advancements in satellite‐based precipitation retrieval algorithms have led to the development of continuous, quasi‐global precipitation products, offering unique opportunities for hydrometeorological and climate research. In this context, six satellite‐based precipitation products (SPPs), including CHIRPS, CMORPH, GSMaP, IMERG, MSWEP, and PERSIANN, were thoroughly investigated for their application in hydrological simulations over the Wardha River basin in India. The observed gridded precipitation product developed by India Meteorological Department (IMD) has been used as reference data to evaluate the performance of SPPs. Hydrological variables such as runoff, soil moisture (SM) and evapotranspiration (ET) were simulated using the Variable Infiltration Capacity model. The performances of SPPs are critically assessed using various statistical metrics, including Pearson's correlation coefficient (R), Klinga‐Gupta Efficiency (KGE), Percent Bias (PBIAS), root mean square error (RMSE), and the RMSE to standard deviation ratio (RSR). The model‐simulated discharge was compared with streamflow observations at a single gauging site, while a spatially distributed comparison was conducted between simulated SM and ET and satellite‐based SM and ET. The IMD dataset consistently shows superior performance for discharge simulation at both daily and monthly scales, with KGE values of 0.85 and 0.91, respectively. Among SPPs, MSWEP and CHIRPS excel in simulating daily and monthly discharge, respectively. For ET simulation, CHIRPS outperforms IMD and other SPPs, achieving an overall KGE value of 0.37. In contrast, PERSIANN is the most effective for simulating SM compared to other precipitation products.

Data-Driven Distributed Predictive Control for Voltage Regulation and Current Sharing in DC Microgrids With Communication Constraints.

The use of nonideal communication networks makes communication constraints become a topical issue in the research of dc microgrids. How to design a distributed secondary control scheme for voltage recovery and accurate current sharing in islanded dc microgrids subject to communication constraints is of interest in this article. In order to restore the bus voltage to the rated value, a nonlinear element is first introduced into the primary control layer. Then, the closed-loop system of primary control is modeled as a data-driven time-varying linear system. Based on the established model, considering communication constraints, a distributed secondary predictive control strategy is developed to achieve accurate current sharing. While actively compensating for network delays and packet losses, the proposed method renders mathematical physical models unnecessary for the traditional predictive control, and simultaneously completes the multitask in dc microgrids. Finally, several case studies are conducted on a hardware microgrid experimental platform, which not only verifies the effectiveness of the designed data-driven predictive control strategy but also tests microgrid properties such as the plug-and-play ability.

Defining geometric gauge theory to accommodate particles, continua, and fields

Gauge theory underpins the quantum field theories of the standard model, and in a previous paper was shown via a geometric approach to describe classical electromagnetism in a form which approximates quantum electrodynamics. Here we formalize and generalize the notion of a geometric gauge theory, then apply this framework to classical physical models, including an improved Lagrangian for matter field electromagnetism. We find a remarkably consistent series of actions, with straightforward limits under which each previous one may be obtained. Ancillary benefits include a gauge-independent Galilean Lagrangian, a geometric interpretation for the unusual metric dependence of four-momentum, a modern treatment of the effects of worldline variation on the four-current, a gauge theory of gravity which includes a matter field, and consistent units for matter field electromagnetism.

Physical Modelling Scenarios of Tsunami Wave Attenuation Induced by Variation of Mangrove Protection Width and Sea Dike

Physical Modelling Scenarios of Tsunami Wave Attenuation Induced by Variation of Mangrove Protection Width and Sea Dike

A Study of Potential Water–Sand Inrush Based on Physical Model Experiments and Numerical Simulations

A Study of Potential Water–Sand Inrush Based on Physical Model Experiments and Numerical Simulations

Thermal dark matter with low-temperature reheating

We explore the production of thermal dark matter (DM) candidates (WIMPs, SIMPs, ELDERs and Cannibals) during cosmic reheating. Assuming a general parametrization for the scaling of the inflaton energy density and the standard model (SM) temperature, we study the requirements for kinetic and chemical DM freeze-out in a model-independent way. For each of the mechanisms, up to two solutions that fit the entire observed DM relic density exist, for a given reheating scenario and DM mass. As an example, we assume a simple particle physics model in which DM interacts with itself and with SM through contact interactions. We find that low-temperature reheating can accommodate a wider range of couplings and larger masses than those permitted in the usual instantaneous high-temperature reheating. This results in DM solutions for WIMPs reaching masses as high as 1014 GeV, whereas for SIMPs and ELDERs, we can reach masses of 1013 GeV. Interestingly, current experimental data already constrain the enlarged parameter space of these models with low-reheating temperatures. Next-generation experiments could further probe these scenarios.

Physical Model Tests of Piles under Freeze–Thaw Cycles Subjected to Individual and Combined Loads

Physical Model Tests of Piles under Freeze–Thaw Cycles Subjected to Individual and Combined Loads

Magnetized dissipative Soret-Dufour effects on Walter’s-B fluid flow over a stretching sheet with nonuniform heat source/sink and thermal radiation under chemical reaction

The main motivation behind this numerical analysis is to disclose the salient magneto-thermo characteristic features of two-dimensional viscous incompressible magnetized Soret and Dufour effects on the boundary layer flow of Walter’s-B fluid over a stretching sheet under the influence of viscous dissipation. The novel physical effects such as nonuniform heat source/sink and magnetic Ohmic heating are included in the governing equations. Further, prescribed surface temperature condition is introduced in the boundary conditions to describe the thermal transport features. However, the deployed non-Newtonian Walter’s-B fluid rheology model finds its innumerable applications in numerous areas of science and engineering including electronic cooling, polymer processing, nuclear reactor cooling, extraction of polymer sheet, plastic sheet drawing, chemical engineering, metallurgy, injection molding and many more. Therefore, authors have motivated with these applications and advantageous of considered fluid model. Hence, an effort is made to describe the dynamic characteristic features of non-Newtonian Walter’s-B rheology model about a stretching sheet. However, present physical flow model produces highly nonlinear coupled two-dimensional partial differential equations and which are not acquiescent to available analytical methods. Owing to this, a robust MATLAB-based BVP4C technique is deployed to produce the appropriate numerical solutions through suitable similarity transformations. The graphical representations of velocity, temperature and concentration profiles along with skin-friction coefficient, Nusselt and Sherwood numbers are presented. Magnifying magnetic number decays the velocity profile and enhances the thermal and concentration fields. Rising viscoelastic parameter diminishes the thermal and concentration fields and magnifies the velocity field. Rising the radiation parameter diminish the thermal field. Magnifying Soret number raises the concentration field. Rising the space and temperature dependent heat source/sink coefficient amplifies the thermal diffusion field. Magnifying Dufour and Eckert numbers amplifies the thermal field. Finally, the guarantee and accuracy of the investigated problem is presented through a comparison with previous studies.

Определение факта насыщения магнитопровода трансформатора тока на основе непрерывного измерения сопротивления цепи намагничивания

Saturation of electromagnetic current transformers in transient modes of operation of an electric power system can lead to incorrect operation of relay protection devices. One of the most promising directions to improve the stability of the operation of relay protection devices in such modes is digital correction of secondary current. Currently, effective methods have been developed to restore the secondary current based on determination of magnetic circuit saturation. However, the practical application of these methods is impossible due to the imperfection of existing methods of secondary current segmentation. Thus, it is urgent to develop a method to determine saturation for implementation of digital correction algorithms for electromagnetic current transformers. To solve the stated problem, methods of mathematical modeling of electrical circuits containing transformers and the small-disturbance theory have been used. Verification of the research results is carried out in the Matlab software package. A mathematical criterion is formulated to determine the saturation of the magnetic circuit of an electromagnetic current transformer based on the inductance of the magnetization circuit. A method of segmentation of the secondary current has been developed for the implementation of digital correction algorithms based on the proposed criterion. The effectiveness of the developed method to determine the saturation of the magnetic circuit of an electromagnetic current transformer using computational experiments in the Matlab software package is demonstrated. It is planned to verify the developed method using a physical model of an electromagnetic current transformer.

Validation of a PGNAA sensor model for bulk material sorting

Global mineral demand is forecast to increase significantly to achieve the transition to renewable energy. Greater volumes of ore of lower grade will have to be mined to meet demand. Techniques to process large volumes of low-grade ore efficiently are being investigated to reduce the cost and impact of mining. One technique is to use sensor information to sort mined material, allowing waste to be discarded early in mineral processing. Prompt gamma neutron activation analysis (PGNAA) is a sensing technique that can provide information on the multi-elemental composition of a bulk sample which can be used for bulk material sorting. This paper presents the development of a Monte Carlo simulation model of a PGNAA sensor for bulk sorting using the Geant4 toolkit. The GEOSCAN sensor (Scantech Australia) was used as a case-study to demonstrate the application of the model. The sensor responses for a range of pure mineral samples (Fe2O3, SiO2, S, Na2CO3 and MnO2) were measured to validate the developed model. The sensitivity of the simulation results to the hadronic and electromagnetic physics models used was tested. It was determined that the PGNAA sensor model can reproduce measurements obtained from the GEOSCAN sensor. In particular, the model can provide a good reproduction of the overall spectral shape and the locations of distinct characteristic peaks. The differences between simulated and experimental results are within 30% on average. It was found that the Geant4 HP neutron model best reproduces the activation peaks observed in experimental measurements. Additionally, the PGNAA spectrum was found to be insensitive to the choice of electromagnetic model for the photon interactions. The validated sensor model provides a useful tool for investigating PGNAA sensor applications including a bulk sorting strategy for new materials, sensor calibration, improvements in signal analysis and optimised sensor design.

CGull: A Non-Flapping Bioinspired Composite Morphing Drone.

Despite the tremendous advances in aircraft design that led to successful powered flights of aircraft as heavy as the Antonov An-225 Mriya, which weighs 640 tons, or as fast as the NASA-X-43A, which reached a record of Mach 9.6, many characteristics of bird flight have yet to be utilized in aircraft designs. These characteristics enable various species of birds to fly efficiently in gusty environments and rapidly change their momentum in flight without having modern thrust vector control (TVC) systems. Vultures and seagulls, as examples of expert gliding birds, can fly for hours, covering more than 100 miles, without a single flap of their wings. Inspired by the Great Black-Backed Gull (GBBG), this paper presents "CGull", a non-flapping unmanned aerial vehicle (UAV) with wing and tail morphing capabilities. A coupled two degree-of-freedom (DOF) morphing mechanism is used in CGull's wings to sweep the middle wing forward and the outer feathered wing backward, replicating the GBBG's wing deformation. A modular two DOF mechanism enables CGull to pitch and tilt its tail. A computational model was first developed in MachUpX to study the effects of wing and tail morphing on the generated forces and moments. Following the biological construction of birds' feathers and bones, CGull's structure is mainly constructed from carbon-fiber composite shells. The successful flight test of the proof-of-concept physical model proved the effectiveness of the proposed morphing mechanisms in controlling the UAV's path.