Field Model Research Articles

On Samples of Satellite Measurement Data for Constructing a Global Model of the Magnetic Field of Mars

On Samples of Satellite Measurement Data for Constructing a Global Model of the Magnetic Field of Mars

Impact of nonextensivity on the transport coefficients of strongly interacting QCD matter

Abstract Tsallis nonextensive statistics is applied to study the transport coefficients of strongly interacting matter within the Polyakov chiral SU(3) quark mean field model (PCQMF). Nonextensivity is introduced within the PCQMF model through a dimensionless $q$ parameter to examine the viscous properties such as shear viscosity ($\eta$), bulk viscosity ($\zeta_b$), and conductive properties, including electrical conductivity ($\sigma_{el}$) and thermal conductivity ($\kappa$). Additionally, some key thermodynamic quantities relevant to the transport coefficients, like the speed of sound ($c_{sq}^2$) and specific heat at constant volume ($c_{vq}$), are calculated. The temperature dependence of the transport coefficients is explored through a kinetic theory approach with the relaxation time approximation. The results are compared to the extensive case where $q$ approaches 1. The nonextensive $q$ parameter is found to have a significant effect on all transport coefficients. We find that the nonextensive behaviour of the medium enhances both specific shear viscosity $\eta/s_q$ as well as conductive coefficients $\sigma_{el}/T$ and $\kappa/T^2$. In contrast, the normalised bulk viscosity $\zeta_b/s_q$ is found to decrease as the nonextensivity of the medium increases. We have also studied the transport coefficients for finite values of chemical potentials. The magnitude of $\eta$, $\sigma_{el}$, and $\kappa$ increases at lower temperatures while $\zeta$ is found to decrease for systems with non-zero chemical potential.

Magnetic signals from oceanic tides: new satellite observations and applications.

The tidal flow of seawater across the Earth's magnetic field induces electric currents and magnetic fields within the ocean and solid Earth. The amplitude and phase of the induced fields depend on the electrical properties of both seawater and the solid Earth, and thus can be used as proxies to study the seabed properties or potentially for monitoring long-term trends in the global ocean climatology. This article presents new global oceanic tidal magnetic field models and their uncertainties for four tidal constituents, including [Formula: see text] and even [Formula: see text], which was not reliably retrieved previously. Models are obtained through a robust least-squares analysis of magnetic field observations from the Swarm and CHAMP satellites using a specially designed data selection scheme. We compare the retrieved magnetic signals with several alternative models reported in the literature. Additionally, we validate them using a series of high-resolution global three-dimensional (3D) electromagnetic simulations and place constraints on the conductivity of the sub-oceanic mantle for all tidal constituents, revealing an excellent agreement between all tidal constituents and the oceanic upper mantle structure.This article is part of the theme issue 'Magnetometric remote sensing of Earth and planetary oceans'.

Analytical Model of Magnetic Field Generated by Racetrack Superconducting Excitation Winding Within Cylindrical Ferromagnetic Boundary Based on Mirror Method

Analytical Model of Magnetic Field Generated by Racetrack Superconducting Excitation Winding Within Cylindrical Ferromagnetic Boundary Based on Mirror Method

A weak bias-magnetized dynamic permeability testing method for detecting and distinguishing inner and outer diameter defects in gas pipelines

Detecting and distinguishing inner diameter (ID) and outer diameter (OD) defects in gas pipelines is crucial for their safe operation. However, current methods such as eddy current testing (ECT) and saturated magnetic flux leakage (MFL) are unable to meet the detection requirements due to the small diameter and low pressure of gas pipelines. Therefore, this paper presents a weak bias-magnetized dynamic permeability testing (DPT) method, using a differential probe with AC coils and magnetic cores to sense varying physical quantities in the ID surface caused by defects. For ID defects, the varying physical quantities include both dynamic permeability and conductivity, whereas for OD defects, it is solely dynamic permeability. This paper thoroughly analyzes the detection principle and completes the coil impedance model. A simulation model for small AC electromagnetic fields with DC bias is established, and an impedance detection instrument is developed for further experimental investigation. The results show that the weak bias-magnetized DPT can detect both ID and OD defects and distinguish them based on clear differences in the signal waveform. Compared to ECT and MFL, the DPT method has the highest ratio of OD to ID defect signal magnitude, indicating minimal signal attenuation as the buried depth of defects increases. Moreover, a pipeline internal inspection device based on DPT has been developed, demonstrating its capability to detect OD defects with a small drag force.

A Hybrid Analytical Model of Open-Circuit Air Gap Magnetic Field of Interior Permanent Magnet Synchronous Motor With Non-Uniform Air Gap Structure Considering Saturation Effect

A Hybrid Analytical Model of Open-Circuit Air Gap Magnetic Field of Interior Permanent Magnet Synchronous Motor With Non-Uniform Air Gap Structure Considering Saturation Effect

Fracture process zone and fracture energy of heterogeneous soft materials

Bio-inspired heterogeneous soft materials are under rapid development due to their superior fracture and fatigue resistance. In the last few years, several kinds of fibrous soft composites in different length scales have been fabricated. However, the fracture behavior and toughening mechanism of this class of materials are still elusive. Here we develop a theoretical model for the crack tip field of fiber reinforced soft composites. The distribution of deformation around the crack tip and released elastic energy during crack propagation are obtained. The fracture process zone and fracture energy are quantified. There is a critical sample height, below which the fracture process zone size and fracture energy are size-dependent, above which they approach material-specific constants: steady-state fracture process zone size and steady-state fracture energy. A formula is derived to relate the steady-state fracture process zone size and parameters of the composite. It is found that both the steady-state fracture process zone size and the critical sample height scale with the fractocohesive length of the composite. The steady-state fracture energy of the composite can be enhanced either by enlarging the fracture process zone size through tuning fiber geometry or by increasing the work to rupture of the fiber through chemical treatment. This work reveals the toughening mechanism of heterogeneous soft materials and paves the way to design soft materials of high fracture energy, high fatigue threshold, and low hysteresis. It also provides a practical guideline for determining the sample size to measure the steady-state fracture energy of heterogeneous soft materials.

Prediction Model for Aero-engine Combustor Temperature Field with Physical Constraints of High Temperature Deviation

Rapidly predicting the temperature field of the aero-engine combustion chamber can assist researchers in quickly understanding the combustion state. Although deep learning methods can solve this problem in some situation, the generalization ability of this method still faces challenges. This research proposes a deep learning prediction scheme with the loss function based on high-temperature deviations for the temperature field of an aero-engine combustion chamber. Comparative results indicate that the network models with high-temperature deviation constraints demonstrate significantly better prediction accuracy outside the learning area compared to network models without physical constraints. The results also demonstrate that the involvement of the physical constraint loss function at different stages of network training has a significant impact on the predictive performance of the network model and generalization ability. Compared to network models trained solely on mean square error, the fully-connected network model with mid-to-late stage of physical constraint training improves by 64.5%, and the optimized attention network model improves by 94.0%.

Tsallis holographic dark energy model in an anisotropic universe with linearly varying deceleration parameter and its correspondence with phantom

In this paper, we investigate a spatially homogeneous and anisotropic Bianchi type-I universe filled with cold dark matter and Tsallis holographic dark energy within the framework of General Relativity. We assume the cold dark matter and the Tsallis holographic dark energy to be non-interacting and obtain exact solutions of the Einstein field equations by considering a linearly varying deceleration parameter. The physical and kinematical properties of the resulting model are explored through different parameters of cosmological importance such as the Hubble parameter, the anisotropy parameter, the equation of state parameter, the jerk parameter, the snap parameter, the lerk parameter etc. The validation or violation of the four energy conditions are also checked. We find that the Weak and Dominant Energy Conditions are fulfilled but the Null and Strong Energy Conditions are violated at late time which supports the accelerated expansion of the universe. In addition, we establish the correspondence between phantom scalar field model and Tsallis holographic dark energy model.

Novel method to estimate horizontal variability of shear wave velocity through multichannel analysis of surface waves

Scale of fluctuations (SOFs) of spatially variable soil properties have been regarded as one of the important parameters for performing reliability-based design in geotechnical engineering. However, the information required to estimate the SOFs in practice is limited, especially in the horizontal direction. In this study, the potential use of Multichannel Analysis of Surface Waves (MASW) to estimate the SOFs of shear wave velocity (VS) in horizontal direction is investigated through a series of numerical investigations. 2D random field models with a vertically increasing trend of VS were first simulated with different levels of variability controlled by the coefficient of variation (COV) and SOF. Afterwards, a large number of numerical MASW tests were performed using a 2D finite difference method, where the survey lines were progressively shifted. Results show that the COV of VS can be determined from the scatter of the dispersion curves, whereas the horizontal SOF of VS can be appropriately estimated from the phase velocity profile presented in the wavelength form. Additionally, in-situ MASW tests were conducted to estimate the horizontal SOF, and the obtained results align with those estimated by different methods. It is highlighted that the accuracy of the estimation depends on survey length. The interpretation using a long array reflects an averaged site condition of the survey area, thus losing the variability information. Favorable predictions are produced when survey length is shorter than 1.0 SOF. However, it should be noted that use of short survey length may limit the depth of investigation.

Two-material structure non-probabilistic reliability-based topology optimization against geometric imperfections with bounded field model

In additive manufacturing processes for multi-material structures, geometric uncertainties such as boundary or interface size deviation inevitably occur in the structure because of processing errors and various other reasons; these uncertainties induce performance fluctuations and affect the reliability of the structure. Considering the limited number of samples in practical engineering projects, a novel method of two-material structure non-probabilistic reliability-based topology optimization (TNRBTO) against geometric uncertainty is proposed to improve structure reliability under conditions in which the geometric uncertainty is characterized by an uncertainty threshold field function and further described by a non-probabilistic bounded field model. TNRBTO is a nested optimization model in which the inner-loop is used for reliability evaluation and the outer loop is used to determine the optimal two-material topology via the material-field series-expansion (MFSE) topology optimization method. The sensitivity information for the TNRBTO model is obtained via adjoint sensitivity analysis, and a gradient-based optimization algorithm based on the method of moving asymptotes (MMA) is used to solve the optimization problem. Numerical examples verified the effectiveness of the TNRBTO model against the geometric uncertainty that exist in two-material structures with bounded field model.

An Analysis of Relationship Quality and Loyalty Between Farmers and Agribusiness Companies in the Rice Industry: Using Multi-Group Analysis

Rice is an important agricultural product in Vietnam; however, the rice industry faces several challenges, particularly weak linkages between farmers and enterprises. The Vietnamese government has introduced the Large Field Model (LFM) program to improve cooperation between farmers and agribusiness companies. Despite these efforts, its implementation remains limited, and contract violations are common. This study investigated the factors affecting relationship quality (RQ) and loyalty (LO) between farmers and agricultural companies in the LFM, focusing on comparing cooperative and non-cooperative participating farmers. Using the Partial Least Squares–Multi-Group Analysis (PLS-MGA) method, this study assessed the different effects of factors such as price satisfaction (PS), payment terms (PTs), and support policies (SPs) on RQ and LO among two groups. The findings indicated that RQ has a stronger influence on LO in farmers with cooperative participation than those who exhibit non-cooperative participation. PS was the most significant factor influencing RQ in both groups, whereas PT was influential only for cooperative participating farmers. SP did not significantly affect RQ in either group. Finally, agricultural companies and policymakers should strengthen partnership management in agricultural supply chains by addressing gaps in support policies, developing appropriate pricing strategies, being flexible in negotiating payment terms, and improving the legal framework related to contract enforcement.

Phase field fracture in elastoplastic solids: a stress-state, strain-rate, and orientation dependent model in explicit dynamics and its applications to additively manufactured metals

Phase field models have gained growing popularity in analysing fracture behaviour of materials. However, few have been explored to simulate dynamic ductile fracture to date. This study aims to develop a phase field framework considering strain rate, stress state, and orientation dependent ductile fracture under dynamic loading. Firstly, governing equations of displacement and phase fields are formulated in an explicit finite element framework. Secondly, constitutive relations are established with a hypoelastic-plasticity framework, encompassing the influence of material orientation and strain rate on both plasticity and fracture initiation. Stress states dependent fracture initiation is also considered. Thirdly, finite element implementation and corotational formulation for constitutive equations are derived. To validate the proposed model, finally, additively manufactured samples, involving material-level and crack propagation specimens are tested under dynamic loading conditions. Overall, the proposed phase field model can properly reproduce the experimental force-displacement curves and crack paths. Uniaxial tension tests reveal that a higher strain rate can lead to a higher hardening curve and lower ductility. Other material specimens further demonstrate the capability to predict stress state and orientation dependent dynamic fracture. To simulate dynamic crack paths accurately, it is necessary to consider anisotropic fracture initiation. Lastly, the phase field model was applied for the first time to predict the dynamic response of triply periodic minimal surface (TPMS) structures. Dynamic crack patterns were effectively captured, and the fracture mechanisms were thoroughly analysed. This study provides an explicit phase field framework for dynamic ductile fracture, with applications to additively manufactured materials and structures.

Empirical Modification of Force Fields for the Development of Peptide‐Based Gas Sensors

AbstractMolecular dynamics models combined with computational approaches can be used as advanced screening techniques for finding highly efficient material‐molecule interactions based on binding affinity, including in the development of gas sensors. However, most models are originally designed for liquid phase interactions, which do not align with gas sensing conditions, resulting in lower‐than‐expected performance. This study introduces an empirical modification method to adjust peptide interaction models for a gas phase, aiming to better accommodate the interaction between pentapeptides and target gas molecules. By adapting the weights of terms in the Gibbs free energy equation given in an empirical force field model, we demonstrate a significant increase in the absolute value of coefficient of determination (R02) , from an average of 0.05 with conventional liquid phase models to 0.90 with proposed gas phase models. An empirical modification technique for gas phase interactions markedly enhances the prediction accuracy of models, facilitating the effective development of peptide‐based gas sensors.

A novel approach for full-core mesh generation to enable high-fidelity thermal-hydraulic simulation of nuclear reactor engineering

Thermal-hydraulic analysis is crucial in reactor engineering. High-fidelity simulations, utilizing advanced computing techniques and supercomputing resources, are highly regarded. High-quality fluid mesh models are essential for complex reactors’ high-fidelity simulations. Using existing tools for model construction has limitations in quality control, performance, user dependency, file generation, and visualization. Estimating time and memory consumption for full-core meshing is also not possible. A R-IMG approach is designed, it effortlessly creates mesh models for intricate flow field, demonstrating exceptional modeling performance, robustness, scalability, and reduced user dependency, while its flexible file manner effectively addresses challenges in generating and visualizing large-scale mesh files. Extensive testing validates R-IMG’s effectiveness and reliability in meshing the reactor’s flow field. It efficiently generates high-quality meshes for the complex flow field in the entire fuel region of CEFR, completing the process within 7 h and 10GB of memory. The resulting model has around 14 billion cells and an average quality of 0.7. R-IMG achieves a maximum parallel scale of 3200 processes for file generation, with approximately 90% parallel efficiency. These results demonstrate that R-IMG outperforms existing tools in core meshing and shows significant potential for full-core meshing. Successful visualization of models and benchmark tests provide evidence for models’ correctness.

Morphology and Properties of the Laser-Irradiated Composition “Chrome Coating — Copper Substrate”

Introduction. During pulsed laser processing and modification of the surface of non-ferrous alloys and coatings based on them, several still unresolved issues arise. In particular, the extreme thermal deformation conditions of laser processing are not linked to the peculiarities of structure formation and formation of properties in irradiated “coating — copper substrate” compositions. A metal physical analysis of the possibility and reasons for increasing the adhesion strength of coatings to a metal (copper) substrate during high-speed laser processing is insufficiently substantiated and evidence-based. To make a reasonable choice of technological parameters for the surface hardening mode of non-ferrous alloy products, as well as for obtaining high-quality workable composite layers on their surface, it is necessary to solve the above issues and tasks. The aim of this article is to determine the possibility and conditions for increasing the adhesion strength of a chrome coating to a copper substrate under laser irradiation of the composition.Materials and Methods. Metal physical studies in the work were carried out on samples of non-ferrous alloys of the Cu–Zn system with a chrome electrochemical coating with a thickness of 20 μm. The “copper substrate — chrome coating” composition was irradiated at a Kvant-16 installation with a radiation power density of 70–250 MW/m2. Metallographic structural analysis, scanning probe microscopy, and durometric studies were used in the work.Results. It has been calculated that the dynamic and thermal stresses arising in the laser-irradiated compositions “chrome coating — copper substrate” were about 320 MPa. Metal physical studies revealed that, in extreme thermal deformation conditions of laser treatment, the effect of contact melting was manifested at the boundary of the coating with the copper base. Dynamic recrystallization occurred in the surface layers of the irradiated L62 copper alloy, resulting in the formation of grains with a size of 4.5–5.0 μm on the surface of the alloy with an initial grain size of 25 μm.Discussion and Conclusion. It has been found that the adhesion strength of a chrome coating to a copper alloy substrate increased laser irradiation at a radiation power density of 150 MW/m2. This was due to the formation of a transition region 2–4 μm deep in the contact zone with a structure consisting of sections of mutually insoluble solid solutions based on chromium and copper. Based on the analysis of the copper —chromium state diagram and the model of the temperature field under laser irradiation of the chromium coating, it was suggested that contact melting occurred in the transition zone from the coating to the copper substrate. It was shown that thermostrictive stresses, the calculated quantitative values of which were about 320 MPa, had an initiating effect on the observed processes of structure formation in the laser irradiation zones. It was found that such a level of stresses arising in copper alloys under laser irradiation was sufficient for plastic deformation and dynamic recrystallization of the metal and contributed to the formation of a fine-grained structure (4.5–5.0 μm) with an initial grain size of 25 μm. An analysis of the results of studies of irradiated compositions "coating — copper substrate" allowed us to conclude that they expanded the technological capabilities of the laser method of hardening materials and ensure guaranteed high performance of irradiated products with coatings

Large-scale field model testing of the effects of soft rock water content on the bearing performance of tunnel-type anchorages

Large-scale field model testing of the effects of soft rock water content on the bearing performance of tunnel-type anchorages

Compartmentalized pooling generates orientation selectivity in wide-field amacrine cells

Orientation is one of the most salient features in visual scenes. Neurons at multiple levels of the visual system detect orientation, but in many cases, the underlying biophysical mechanisms remain unresolved. Here, we studied mechanisms for orientation detection at the earliest stage in the visual system, in B/K wide-field amacrine cells (B/K WACs), a group of giant, nonspiking interneurons in the mouse retina that coexpress Bhlhe22 (B) and Kappa Opioid Receptor (K). B/K WACs exhibit orientation-tuned calcium signals along their long, straight, unbranching dendrites, which contain both synaptic inputs and outputs. Simultaneous dendritic calcium imaging and somatic voltage recordings reveal that individual B/K dendrites are electrotonically isolated, exhibiting a spatially confined yet extended receptive field along the dendrite, which we term "compartmentalized pooling." Further, the receptive field of a B/K WAC dendrite exhibits center-surround antagonism. Phenomenological receptive field models demonstrate that compartmentalized pooling generates orientation selectivity, and center-surround antagonism shapes band-pass spatial frequency tuning. At the microcircuit level, B/K WACs receive excitation driven by one contrast polarity (e.g., "ON") and glycinergic inhibition driven by the opposite polarity (e.g., "OFF"). However, this "crossover" inhibition is not essential for generating orientation selectivity. A minimal biophysical model reproduced compartmentalized pooling from feedforward excitatory inputs combined with a substantial increase in the specific membrane resistance between somatic and dendritic compartments. Collectively, our results reveal the biophysical mechanism for generating orientation selectivity in dendrites of B/K WACs, enriching our understanding of the diverse strategies employed throughout the visual system to detect orientation.

QCD phase transition with nonextensive NJL model in the strong magnetic field

In this work we make use of the Nambu–Jona-Lasinio model to investigate thermodynamic properties of magnetized three-flavor quark matter. The nonequilibrium Tsallis distribution is characterized by a dimensionless nonextensive parameter q. We find that the system always undergoes a crossover transition for all given q values and the pseudocritical temperature decreases with the increasing nonextensive parameter. We show the variation of the pressure and its anisotropy in parallel and perpendicular directions. However, the diamagnetic nature appears within a certain temperature range at zero chemical potential. Moreover, strong magnetic fields can affect the property of a nonextensive system by changing the magnetization significantly. At high temperatures, the paramagnetic nature always occurs no matter how strong the magnetic field is. Finally, we study the effects of nonextensive parameter q on the trace anomaly and the speed of sound of the system. Published by the American Physical Society 2024

Theoretical studies of two phase-independent frequency spectrum models in atomic selective photoionization processes

Abstract The laser frequency spectrum, whose full width at half-maximum in the frequency domain is laser bandwidth, plays a critical role in atomic multi-step photoionization processes, and it has a significant influence on isotopic selective photoionization results. In this study, two phase-independent frequency spectrum models, that is, mode jitter model based on the “mode jitter” phenomenon and the multi-longitudinal mode model based on multi-longitudinal mode output, are proposed for describing the spectral characteristics in the frequency domain. In the mode jitter model, it is assumed that there is a varying longitudinal mode in every laser pulse, with different central frequencies between adjacent pulses in the pulse train; in the multi-longitudinal model, it is assumed that multiple longitudinal modes are output simultaneously with fixed central frequencies. Selective photoionization properties of these two frequency spectrum models and the chaotic field model are simulated and compared with each other under the Lorentzian frequency spectrum condition. Influences of the excitation intensity, laser frequency spectral line-shape, and cut-off frequency on selective photoionization processes are calculated and compared among the above-mentioned three frequency spectrum models. Finally, the measurement of the laser frequency spectrum and the introduction of individual longitudinal mode’s bandwidth are discussed.