Field Modeling Research Articles

Numerical simulation of the oil pipeline temperature field for the thermal method of measuring the thickness of paraffin deposits taken into account of oil movement

The article provides an analysis of the problems of precipitation of asphaltresin-paraffin deposits on the inner surface of the walls pipelines. The problem of numerical modeling of the temperature field of the heated oil pipeline in the ANSYS software product is considered. The process of heating and cooling the pipeline at different sediment thicknesses and oil velocities is investigated. A two-dimensional numerical model of the oil pipeline has been developed, which allows studying the behavior of its temperature field during heating and cooling. The research developed in the article helps to reduce the cost of maintaining oil pipelines.

Phase field modeling of sub-parabolic oxidation kinetics and in-plane stress in Zircaloy under neutron/proton irradiation

Abstract A detailed study of the sub-parabolic oxidation kinetics in Zircaloy system has been carried out by using phase field modeling under conditions related to oxidation in autoclave and during neutron/proton irradiation. The exploited phase field model is factored in temperature gradient and voltage change between metal and oxide surface. It is shown that the irradiation accelerates oxidation rate and induces development of conjugated in-plane stress. It is found that both in-plane and tensile stresses result in a power-law decrease in a critical time for fragmentation \emph{versus} dose rate. 
It is shown that a critical crystallite size for the related tetragonal to monoclinic phase transformation at the oxide/metal interface decreases with the dose rate. Obtained results correlate well with experimental observations in the reference points and can be exploited to estimate corrosion resistance linked to transformation to monoclinic structure and fragmentation in zirconium-based cladding materials. 
This study provides a deep insight into the details of oxidation kinetics at irradiation in zirconium alloys.

B-10-Based Macrostructured Cathode for Neutron Detectors

This paper focuses on the search for the desired thickness of the 10B4C thin-film coating, as well as the macrostructuring of the aluminum foil substrate used as a cathode in the production of a multiwire gas detector of thermal neutrons. The impact of the 10B4C film thickness from 1.0 to 2.5 μm and of the 0.05 mm thick Λ-shaped macrostructured aluminum foil substrate with an angle at the Λ-vertex from 10 to 45 degrees, with a height from 0.5 to 4 mm and a distance between the Λ-structures from 0.1 to 0.8 relative units on the neutron registration efficiency 1.8Å, was investigated. Numerical modeling of the electrostatic field was carried out using the Elcut software package. The interaction of neutrons with the 10B4C thin-film coating was modeled using the Monte Carlo method in the Geant4 program. The optimal values of the geometrical parameters for the best neutron registration efficiency were determined.

Three-Variate Nonstationary Probabilistic Wind Field Modeling with Time-Varying Spatial Coherence via the NUFFT-Enhanced Stochastic Wave–Based Spectral Representation Method

Three-Variate Nonstationary Probabilistic Wind Field Modeling with Time-Varying Spatial Coherence via the NUFFT-Enhanced Stochastic Wave–Based Spectral Representation Method

Evaluating best management practices for nutrient load reductions in tile-drained watersheds of the Laurentian Great Lakes Basin: A literature review.

Tile drainage systems are extensively implemented across the Laurentian Great Lakes Basin (GLB) to enhance agricultural productivity on poorly drained soils. However, these systems substantially contribute to excess nutrient runoff, particularly phosphorus (P) and nitrogen (N), exacerbating eutrophication and harmful algal blooms in the Great Lakes. This literature review synthesized current knowledge on nutrient loadings from tile-drained agricultural watersheds and evaluated the effectiveness of various agricultural best management practices (BMPs) in mitigating nutrient losses in the GLB. Through a meta-synthesis of field and watershed scale monitoring and modeling studies and statistical analysis using Box-Whisker plots and Monte Carlo simulations, we assessed the nutrient reduction potential of representative BMPs, including cover cropping, nutrient management, controlled drainage, and constructed wetlands in tile-drained landscapes. Findings indicated that individual BMPs substantially reduced nutrient loadings, but the effectiveness of these BMPs depended on site-specific factors, including climate conditions, soil type, and drainage system design. Integrated approaches at field, edge-of-field, and watershed scales with a combination of multiple BMPs enhanced nutrient reduction benefits, aligning with regional water quality targets. The review also highlighted the challenges of climate change that may undermine BMP performance by altering precipitation patterns and increasing extreme weather events. To address these complexities, we proposed a framework for developing adaptive BMP scenarios tailored to specific watershed conditions, emphasizing the need for long-term monitoring and hydrologic model enhancements. This framework was designed to help policymakers, stakeholders, and farmers protect water quality and balance agricultural productivity in the GLB and similar agricultural regions globally.

Enhancing Mars Gravity Field Solutions with China’s Tianwen-1 Tracking Data

Abstract The Tianwen-1 (TW1) mission, which successfully entered Mars's orbit in 2021, provides a valuable data set for enhancing the understanding of Mars’s gravity field. The highly elliptical near-polar orbit of the TW1 orbiter offers unique sensitivity to long-wavelength gravity signals, complementing the contributions of low-altitude missions like the Mars Reconnaissance Orbiter (MRO). In this study, we used 4 months of TW1 radio tracking data in combination with MRO data to develop a new Mars gravity field model up to degree and order 50. We evaluated the improvement of gravity field determination through power spectrum analysis, gravity anomaly maps, and trajectory precision assessment. The result shows significant improvements in accuracy up to degree and order 30, with an average enhancement of 38% in the zonal harmonic coefficients. There are obvious differences between the two gravity field models in gravity anomaly maps. The range of gravity anomaly errors improves after incorporating TW1 data, with the maximum error decreasing from 53.4 to 46.4 mGal and the average error improving from 8.4 to 7.3 mGal. Additionally, orbit determination experiments confirm that the fused gravity field model enhances trajectory modeling for both MRO and TW1. These findings highlight the scientific value of TW1 tracking data in advancing Mars’s gravity field modeling and provide critical insights for future deep-space missions.

Weak evidence for a relationship between group size and flight initiation distance in response to underwater human presence in an exploited fish species

Group size can influence flight initiation distance (FID), a key antipredator behavior, in many animal species. In fishes, however, the effect of group size on FID remains unclear. Two different mechanisms might explain a putative relationship between group size and FID. If fish benefited from having more vigilant individuals around, we would expect group size to be positively associated with FID (considering collective vigilance in the context of the many eyes hypothesis). By contrast, if fish benefited from a predator dilution effect, we would expect group size to be negatively associated with FID. Importantly, such relationships should be critically sensitive to background risk levels. We capitalized on FID observations inside and outside marine protected areas and simulated risk by having a risky spearfisher or a non-risky snorkeler swim towards white seabream (Diplodus sargus) to estimate the relationship between FID and group size. Model selection provides weak evidence that group size positively influences FID of white seabream when group size was modelled two ways: categorically (alone vs. shoal), and continuously (range 2–15). While the results suggest that overall group size has a measurable impact on FID, the presence of spearfishers or snorkelers had a weak effect on the relationship of group size and FID, which seems to be more sensitive exclusively to the protection level (inside/outside marine protected areas). Our findings align with previous studies showing mixed results on the relationship between group size and FID. This study underscores the complexity of antipredator behaviors in natural settings and suggests that multiple interlinked factors, rather than group size alone, drive FID in fishes. Future research should integrate field observations, laboratory experiments, and modeling to study the ecological influence of group size on FID more comprehensively.

Implementation of the BIRCH algorithm to construct a data-adaptive network design for regional gravity field modeling via SRBF

This study presents a new methodology to establish an optimal network for the spherical radial basis functions (SRBFs) by employing the Balanced Iterative Reducing and Clustering using Hierarchies (BIRCH) algorithm. In the proposed methodology, sub-cluster centers obtained by the BIRCH algorithm are replaced with the center of the SRBFs. Since the horizontal positions of the observations are utilized in the clustering, the SRBFs are distributed adaptively to the data. The algorithm’s performance and the effects of the BIRCH parameters are investigated in detail with real and simulated data sets in the Auvergne and Colorado areas, respectively. The bandwidth of each SRBF is determined by the generalized cross-validation (GCV) technique. The turning point algorithm is employed to reduce long-wavelength errors that occur due to the always positivity of the selected Legendre coefficients in the spatial domain. The outcomes of the numerical tests show that only one parameter (threshold) is enough to construct a proper data-adaptive network design for SRBFs. Compared to existing algorithms, fewer SRBFs are required to achieve the same accuracy on the control points while saving more than 95% of the time in the network design. Furthermore, the proposed methodology improves the condition number of the normal equation matrix. That makes it possible to estimate unknown coefficients without regularization in the least-square procedure depending on the selected threshold parameter. Therefore, the BIRCH algorithm is very effective and suitable to establish an optimal data-adaptive network design, especially in large data sets.

Electromagnetic Field Modeling and Optimization Design of Axial Magnetic Flux Eddy Current Brake Considering Non‐Ideal Factors

Accurate analytical calculation of electromagnetic field is the basis of research and optimization of axial magnetic flux eddy current brake, and structural optimization design is the key to improving system performance and reducing engineering construction costs. In order to establish an accurate analytical calculation model of electromagnetic field of axial magnetic flux eddy current brake, based on the two‐dimensional analytical calculation model of electromagnetic field, this paper comprehensively considers the influence of non‐ideal factors such as core saturation, transverse dynamic end effect and secondary skin effect on the electromagnetic characteristics of axial magnetic flux eddy current brake, and obtains an improved analytical calculation model of electromagnetic field by introducing corresponding correction coefficients, and verifies the accuracy of the analytical calculation model of electromagnetic field by comparing with the numerical calculation results of three‐dimensional electromagnetic field finite element model. On this basis, an improved multi‐objective particle swarm optimization algorithm is adopted to optimize the system design, so as to increase the electromagnetic braking torque, reduce the electromagnetic axial force and reduce the secondary mass. Finally, the accuracy of the above electromagnetic field analytical calculation model and optimization design results is verified on the experimental research platform of axial magnetic flux eddy current brake, which can provide theoretical basis for subsequent researchers to design and optimize the electromagnetic scheme. © 2025 Institute of Electrical Engineers of Japan and Wiley Periodicals LLC.

Effectiveness of agricultural BMPs on phosphorus load reduction for the Canadian Lake Erie basin: A literature review

Lake Erie, the shallowest and warmest of the Great Lakes, has been increasingly threatened by eutrophication and harmful algal blooms affecting economic growth in the region. Excess nutrients, particularly phosphorus, transported with agricultural runoffs have become a major issue of lake water quality. In response to this growing concern over the adverse environmental effects of agriculture, farmers, conservation authorities and governments have worked together to promote and implement best or beneficial management practices (BMPs) in the contributing watersheds that focus on maintaining agricultural activity and farm profitability while protecting the environment. This paper conducted a technical review of BMPs and their effectiveness on phosphorus load reduction from agricultural fields for the Canadian Lake Erie Basin (CLEB). These BMPs include cover crop, conservation tillage, manure incorporation, crop nutrient planning, fragile land retirement, adding organic amendments, reducing soil compaction, controlled tile drain, grassed waterway, vegetative filter strip, riparian buffer, water and sediment control basin, and wetland restoration. Field experiments and modeling studies about BMP effectiveness on phosphorus load reduction from agricultural fields in the CLEB and the Great Lakes region were reviewed and assessed. Findings from other similar geographic regions were also documented for comparison and reference. Because BMPs are site-specific, their phosphorus load reduction effectiveness varied over a wide range in the literature depending upon characteristics of the BMP and local climate, slope, soil type, land use, and land management conditions. Based on the literature review, factors influencing BMP effectiveness were analyzed, and suggestions on research priorities for evaluating BMP effectiveness in the CLEB were provided. This study will benefit decision-makers, watershed conservation authorities, and other stakeholders in estimating phosphorus load reductions from agricultural landscapes and contribute to tracking progress toward achieving Canada’s phosphorus load reduction targets for Lake Erie.

SUBSTITUTION OF OPTIMIZATION CRITERIA FOR UAV INFORMATION PROCESSING SYSTEMS TAKING INTO ACCOUNT INFORMATION CHARACTERISTICS OF OUTPUT INFORMATION

The use of UAVs with combined navigation systems during the repulsion of large-scale armed aggression of the Russian Federation was analyzed. The models of description of information features for correlation-extreme navigation systems were analyzed. The characteristics of different types of objects and backgrounds of the sighting surface were determined. The general principles that determine the description of the sighting surface of any type were formulated. It was shown that current images formed using informative features should be described using the same indicator. An approach to describing the sighting surface through brightness was developed, separately for each channel of correlation-extreme navigation systems, which are formed by information sensors. Analytical expressions for the current image in each information sensor of correlation-extreme navigation systems are given. The results of numerical modeling of brightness and contrast distributions for a randomly selected section of the sighting surface are given. The results of numerical modeling of correlation analysis fields of brightness, contrast and fractal dimension for selected objects on the viewing surface are presented. The results of numerical modeling were analyzed and conclusions were drawn on its basis regarding the dependence of information features on changes in UAV navigation parameters and the influence of obstacles. The dependence of information features on changes in UAV navigation parameters and interference effects is confirmed. This means that the formation of a set of reference images taking into account the navigation and angular parameters of the UAV orientation and the influence of interference is possible in accordance with the selected information features. But minimizing the number of fragments of reference images in the set requires determining the degree of coincidence of the compared images, which necessitates solving the problem of determining this indicator and its thresholds, the use of which will ensure the formation of a unimodal decision function, or a decision function with several maxima, the use of which in further processing will ensure the determination of the global maximum of the decision function. The results obtained can be used for further development and optimization of subsystems for detecting and processing information and forming UAV control signals in difficult interference conditions. They can be useful for creating new approaches to increasing the accuracy and probability of location of modern and promising air attack means produced by the state.

Visuospatial computations vary by category and stream and continue to develop in adolescence.

Reading, face recognition, and navigation are supported by visuospatial computations in category-selective regions across ventral, lateral, and dorsal visual streams. However, the nature of visuospatial computations across streams and their development in adolescence remain unknown. Using fMRI and population receptive field (pRF) modeling in adolescents and adults, we estimate pRFs in high-level visual cortex and determine their development. Results reveal that pRF location, size, and visual field coverage vary across category, stream, and hemisphere in both adolescents and adults. While pRF location is mature by adolescence, pRF size and visual field coverage continue to develop - increasing in face-selective and decreasing in place-selective regions - alongside similar development of category selectivity. These findings provide a timeline for differential development of visual functions and suggest that visuospatial computations in high-level visual cortex continue to be optimized to accommodate both category and stream demands through adolescence.

ЕЛЕКТРОСТАТИЧНЕ ПОЛЕ В ПОВІТРЯНОМУ ПРОМІЖКУ СИСТЕМИ ПЛОСКО-ПАРАЛЕЛЬНИХ ЕЛЕКТРОДІВ ДЛЯ ОБРОБКИ КРАПЕЛЬ ВОДИ БАР’ЄРНИМ РОЗРЯДОМ

This study investigates the electrostatic field in a discharge chamber (DC) designed for water purification from organic pollutants using pulsed barrier discharge (PBD) technology. The DC consists of vertical plane-parallel electrodes, with an air gap containing water droplets between them, and one of the electrodes is insulated from the air gap by a dielectric (barrier). The research employs computer modeling in both two-dimensional and three-dimensional setups. Therefore, the aim of this work is to compare the distribution of the electrostatic field intensity of PBD in the air gap and the electrical capacitance of the DC to establish the optimal distance between droplets and to determine the calculation error using the two-dimensional DC model. Electrostatic field modeling was performed using the Poisson equation and the finite element method. Calculations were performed for two-dimensional and three-dimensional models with conditions of a droplet diameter of 1 mm, a gas gap length of 3.36 mm, and an applied voltage of 3 kV. The influence of droplet conductivity and the distance between them on the characteristics of the electrostatic field in the gas medium and in the droplets was investigated. A comparison of the calculated capacitance values of the DC in the two-dimensional and three-dimensional models depending on the distance between the droplets was conducted. The research results can be used in the application of electro-discharge technology based on pulsed barrier discharges in water treatment systems, specifically in selecting the parameters for the movement of the treated liquid in the plasma zone. References 10, figures 7.

INTEGRATING LOW-IMPACT DEVELOPMENT TECHNIQUES IN HERITAGE SITES: INSIGHTS FROM THE DIENG TEMPLE COMPLEX

The Dieng Temple Complex is a significant archaeological site representing ancient Hindu influences, located on the Dieng Plateau, Central Java. Due to its high elevation and associated environmental conditions, the complex faces specific hydro-geotechnical challenges. This study assesses the impacts of proposed development activities within the complex, especially on the hydrological parameters. Field evaluations and modelling by Environmental Protection Agency Stormwater Management Model (EPA SWMM) software are conducted during the study. The results indicate that the current conditions exhibit minimal hydrological impacts. However, the proposed developments could substantially increase the impervious surface and modify surface runoff patterns. Along with the development plan, sustainable practices to minimise the risks are to be implemented. Implementing Low-Impact Development (LID) techniques may mitigate the effects mentioned earlier. It is recommended that the integration of sustainable practices be stressed to preserve the cultural and environmental integrity of the Dieng Temple Complex. This approach balances developmental aspirations with conservation imperatives, ensuring that the site’s historical and cultural significance is preserved. By adopting these measures, the Dieng Temple Complex can maintain its status as a vital site for researchers, historians, and tourists interested in Indonesia’s early history while also supporting the local community’s economic welfare through sustainable development practices

Multispheroidal model of magnetic field of uncertain extended energy-saturated technical object

Problem. The implementation of strict requirements for magnetic silence of elongated energy-saturated technical objects – such as naval vessel and submarines is largely determined by the adequacy of mathematical models to the signatures of a real magnetic field. Aim. Simplification of mathematical modeling of the magnetic field of an uncertain extended energy-saturated object based on the development and application of a multispheroidal model of its magnetic field instead of the well-known multidipole model. Methodology. Coordinates of the geometric location and magnitudes of spatial extended spheroidal harmonics of spheroidal sources of multispheroidal model of magnetic field calculated as magnetostatics geometric inverse problems solution in the form of nonlinear minimax optimization problem based on near field measurements for prediction far extended technical objects magnetic field magnitude. Nonlinear objective function calculated as the weighted sum of squared residuals between the measured and predicted magnetic field COMSOL Multiphysics software package used. Nonlinear minimax optimization problems solutions calculated based on particle swarm nonlinear optimization algorithms. Results. Results of prediction far magnetic field magnitude of extended technical objects based on designed multispheroidal model of the magnetic field in the form of spatial prolate spheroidal harmonics in prolate spheroidal coordinate system using near field measurements with consideration of extended technical objects magnetic characteristics uncertainty. Originality. For the first time the method for design of multispheroidal model of magnetic field of uncertain extended energy-saturated technical object based on magnetostatics geometric inverse problems solution and magnetic field spatial spheroidal harmonics calculated in prolate spheroidal coordinate system taking into account of technical objects magnetic characteristics uncertainties developed. Practical value. It is shown the possibility to reduce the number of spheroidal sources of the magnetic field for adequate modeling of the real magnetic field based on the developed multispheroidal model compared to the number of well-known dipole sources of the magnetic field in the multidipole model of the magnetic field. References 48, figures 4.

Numerical modeling and experimental study of thermal field and material removal for silicon wafer in final-touch polishing

Numerical modeling and experimental study of thermal field and material removal for silicon wafer in final-touch polishing

Discretization-independent surrogate modeling of physical fields around variable geometries using coordinate-based networks

Abstract Numerical solutions of partial differential equations require expensive simulations, limiting their application in design optimization, model-based control, and large-scale inverse problems. Surrogate modeling techniques aim to decrease computational expense while retaining dominant solution features and characteristics. Existing frameworks based on convolutional neural networks and snapshot-matrix decomposition often rely on lossy pixelization and data-preprocessing, limiting their effectiveness in realistic engineering scenarios. Recently, coordinate-based multilayer perceptron networks have been found to be effective at representing 3D objects and scenes by regressing volumetric implicit fields. These concepts are leveraged and adapted in the context of physical-field surrogate modeling. Two methods toward generalization are proposed and compared: design-variable multilayer perceptron (DV-MLP) and design-variable hypernetworks (DVH). Each method utilizes a main network which consumes pointwise spatial information to provide a continuous representation of the solution field, allowing discretization independence and a decoupling of solution and model size. DV-MLP achieves generalization through the use of a design-variable embedding vector, while DVH conditions the main network weights on the design variables using a hypernetwork. The methods are applied to predict steady-state solutions around complex, parametrically defined geometries on non-parametrically-defined meshes, with model predictions obtained in less than a second. The incorporation of random Fourier features greatly enhanced prediction and generalization accuracy for both approaches. DVH models have more trainable weights than a similar DV-MLP model, but an efficient batch-by-case training method allows DVH to be trained in a similar amount of time as DV-MLP. A vehicle aerodynamics test problem is chosen to assess the method’s feasibility. Both methods exhibit promising potential as viable options for surrogate modeling, being able to process snapshots of data that correspond to different mesh topologies.

Impact of Heterosigma akashiwo on the environmental behavior of microplastics: Aggregation, sinking, and resuspension dynamics.

Aggregation processes of microalgae have significant effects on the vertical distribution of microplastics (MPs) in the marine environment. This study explored how the harmful microalga Heterosigma akashiwo affects the aggregation and sinking characteristics of four types of MPs: low and high-density polyethylene (PE) spheres, and small and large polypropylene (PP) fragments. The aggregation of MPs was primarily driven by extracellular polymeric substances (EPS) rather than direct attachment to the cells, contributing to their sinking. The sinking of low-density PE spheres followed a logistic function, saturating at 28 % with a half-saturation time of 9 days. In contrast, small PP fragments sank minimally (under 2 %) and large PP fragments showed almost no sinking, indicating the varying impacts of MP density and size. The sinking velocity of the MP aggregates was significantly lower for low-density PE spheres (0.63 mm∙s-1) than for high-density PE spheres (0.81 mm∙s-1), despite no significant differences in aggregate size or MP particle number. This result may suggest that low-density MPs could potentially affect marine carbon cycle. Furthermore, no clear evidence was found for the resuspension of the settled aggregates due to bacterial decomposition under dark and cold conditions. As the first experimental study to explore the aggregation, sinking, and resuspension of different MPs in the presence of H. akashiwo, these findings, when integrated with field observations and modeling studies, provide valuable insights for predicting MP distribution in marine environments.

QPRF: A system to accelerate population receptive field modeling.

BOLD response can be fitted using the population receptive field (PRF) model to reveal how visual input is represented on the cortex (Dumoulin and Wandell, 2008). Fitting the PRF model costs considerable time, often requiring days to analyze BOLD signals for a small cohort of subjects. We introduce the qPRF ("quick PRF"), a system for accelerated PRF modeling that reduced the computation time by a factor >1,000 without losing goodness-of-fit when compared to another widely available PRF modeling package (Kay et al., 2013) on a benchmark of data from the Human Connectome Project (HCP; Van Essen et al. (2013). The system achieves this level of acceleration by pre-computing a tree-like data structure, which it rapidly searches during the fitting step for an optimal parameter combination. We tested the method on a constrained four-parameter version of the PRF model (Strategy 1 herein) and an unconstrained five-parameter PRF model, which the qPRF fitted at comparable speed (Strategy 2). We show how an additional search step can guarantee optimality of qPRF solutions with little additional time cost (Strategy 3). To assess the quality of qPRF solutions, we compared our Strategy 1 solutions to those provided by Benson et al. (2018) who performed a similar four-parameter fit. Both hemispheres of the 181 subjects in the HCP dataset (a total of 10,753,572 vertices, each with a unique BOLD time series of 1800 frames) were analyzed by qPRF in 12.82 h on an ordinary CPU. The absolute difference in R2 achieved by the qPRF compared to Benson et al. (2018) was negligible, with a median of 0.025% (R2 units being between 0% and 100%). In general, the qPRF yielded a slightly better fitting solution, achieving a greater R2 on 70.2% of vertices. We also assess the qPRF method's model-recovery ability using a simulated dataset. The qPRF may facilitate the development and use of more elaborate models based on the PRF framework and may pave the way for novel clinical applications.

Atomistic-informed phase field modeling of magnesium twin growth by disconnections

The nucleation and propagation of disconnections play an essential role during twin growth. Atomistic methods can reveal such small structural features on twin facets and model their motion, yet are limited by the simulation length and time scales. Alternatively, mesoscale modeling approaches (such as the phase field method) address these constraints of atomistic simulations and can maintain atomic-level accuracy when integrated with atomic-level information. In this work, a phase field model is used to simulate the disconnection-mediated twinning, informed by molecular dynamics (MD) simulations. This work considers the specific case of the growth of {101¯2} twin in magnesium. MD simulations are first conducted to obtain the orientation-dependent interface mobility and motion threshold, and to simulate twin embryo growth and collect facet velocities, which can be used for calibrating the continuum model. The phase field disconnections model, based on the principle of minimum dissipation potential, provides the theoretical framework. This model incorporates a nonconvex grain boundary energy, elasticity and shear coupling, and simulates disconnections as a natural emergence under the elastic driving force. The phase field model is further optimized by including the anisotropic interface mobility and motion threshold suggested by MD simulations. Results agree with MD simulations of twin embryo growth in the aspects of final twin thickness, twin shape, and twin size, as well as the kinetic behavior of twin boundaries and twin tips. The simulated twin microstructure is also consistent with experimental observations, demonstrating the fidelity of the model.