Field Modeling Method Research Articles

Theoretical basis for phase field modeling of polycrystalline grain growth using a spherical-Gaussian-based 5-D computational approach

Using a previously developed phase field modeling method, where interface energies are described by spherical gaussians that allow the modeling of complex anisotropies, a new phase field model was developed to model 5-D anisotropy in polycrystalline grain growth. We present the use of quaternions, assigned to individual grains as orientations and misorientations for grain boundaries, as a means of simulating the ongoing mesoscale changes during anisotropic polycrystalline grain growth. The full 5-D landscape is scanned in MATLAB, and the grain boundary (GB) energy of each grain boundary is calculated from the continuous function developed by Bulatov et al. MATLAB is then used to find all local minima in the GB energy which are stored for use in the phase field model. The methodology of including these minima in the phase field model involves using 2-D gaussian switches, which match the misorientation between grains with misorientations for the GB energy minima. Within a threshold range of the minima misorientation, the switch activates a spherical Gaussian to set the GB energy to the desired value creating in combination a full 5D GB energy space. This creates a GB energy that morphs in real time and space as the GB plane or grain orientations change. Implementation methods of the model are outlined for the Multiphysics Object Oriented Simulation Environment (MOOSE), where reduced order parameters still retain individual grain identification useful for individually assigned quaternions.

Environment Potential Field Modeling for Ship Automatic Collision Avoidance in Restricted Waters

The accurate environment potential field (EPF) modeling method and highly efficient collision avoidance (CA) approach are key technologies for maritime autonomous surface ships (MASS). A novel and accurate environment potential field (EPF) model is proposed using electronic navigation chart (ENC) face objects to describe different types of navigable and non-navigable areas, and an improved artificial potential field (APF) method is presented to realize collaborative CA and obstacle avoidance (OA). Implicit equations of complex-shaped face objects were constructed based on R-function theory, and the discrete-convex hull method was introduced to realize automatic EPF modeling. Collaborative CA and OA experiments in restricted waters were conducted on a ship handling simulator. The results show that the improved APF method can obtain a robust and deterministic collision-free path under different weather conditions and in restricted waters, and the track zone width remains within 0.1 nm. The proposed face object EPF model is efficient and accurate, even with numerous vertices and complex shapes, and can drive the ship apart at a relatively safe distance in accordance with the recommended CA parameter. We present a practical CA approach and an effective EPF modeling method for APF-based ship path planning.

Novel meta-analytic electric field modeling method to identify prefrontal cortex regions related to working memory performance

Novel meta-analytic electric field modeling method to identify prefrontal cortex regions related to working memory performance

Multi-objective optimization of ship magnetic field modeling method

Ship magnetic field modeling is not only beneficial to understanding the characteristics of ship magnetic field, but also can predict the space distribution of ship magnetic field, which has an important application in ship protection and underwater weapons. Aiming at the problems of low modeling accuracy and poor stability in establishing the ship magnetic field hybrid model, a method of establishing a high precision stablity model is proposed in this paper. A hybrid model of magnetic field of a ship is established by using a uniformly magnetized rotating ellipsoid and a magnetic dipole array. Since the number and positions of magnetic dipoles in the hybrid model have an important effect on the modeling accuracy and stability, the fitting error function representing the modeling accuracy and the coefficient matrix condition number function representing the stability of the model are constructed by taking the magnetic dipole parameters as unknown variables. The multi-objective function is constructed by combining the fitting error function with the coefficient matrix conditional number function, which indirectly transforms the modeling problem into a multi-objective optimization problem. The multi-objective function is solved by using the multi-objective particle swarm optimization algorithm, and an optional set of modeling solution results is obtained. In order to select the best results from the optional set, the corresponding selection rules are designed based on the modeling accuracy. The proposed method is validated by the measured data of three kinds of ship models, the modeling results show that the relative error of the model is less than 3%, and the conversion error is less than 6%, which verifies that the proposed method can effectively model the ship magnetic field. Though the measurement data error exists, the modeling solution results from the proposed method have the best stability, which verifies that the modeling method proposed in this work has good stability. Compared with the two existing modeling methods, the proposed method has very good modeling accuracy and stability. Finally, the actual data of a ship on the sea are used for modeling, and the modeling results further verify that the proposed method has high modeling accuracy and conversion accuracy, and can be effectively applied to the relevant projects.

Combined Merits of High Dielectric Breakdown Strength and Low Sintering Temperature Acquired in Mgo-Baseddielectric Ceramics: From Theoretical Prediction to Experimental Validation

Dilemma of dielectric breakdown has perplexed researchers for decades while intrinsic factors accounting for dielectric breakdown strength (DBS) is still unsettled. In this work to address the great deterioration of DBS after LiF acceptor doping in MgO (LMO), high throughout first principles calculation is carried out to screen nearly 30 cations from donor doping perspective. The work function from the theoretical calculation, as a descriptor correlated to electronic property, displays a linear correlation with experimental DBS while Mn is proven to be the best candidate dopant for its greatly improvement on work function of LMO system and therefore a markedly enhanced DBS. Detailed analysis manifests that MnCO3 incorporation further decreases the sintering temperature of LMO to 900 °C and also leads to defect associations between oxygen vacancies and cation substitutional defects, causing distinct change in dielectric behavior and conduction mechanism. Afterwards, beneficial effects of grain refinement and increased grain boundary resistivity on DBS are analyzed using phase field modeling method. With all these merits, nearly 85% improvement in DBS is achieved in 1 wt% MnCO3 tailored LMO. This work not only reveals the decisive role of work function in DBS prediction therefore shed light on composition design of dielectrics, but also provides a paradigm combining ions screening, theoretical prediction, experiments and simulation together to greatly accelerate the materials research.

Small Scale Rain Field Sensing and Tomographic Reconstruction with Passive Geostationary Satellite Receivers

Sensing of the rain rate and the movement of the rain field over a relatively small geographical area may often be necessary for agricultural purposes, water management objectives or transport management in airports or harbors. In this paper, an entirely passive method is suggested to sense rainfall rate and extension of a rain field, with reconstruction in two dimensions using a tomographic method. In order to achieve this goal, multiple colocated satellite receivers are proposed to measure the beacon signal levels of geostationary satellites received at different azimuth angles. The tomographic reconstruction of the rain field takes the advantage of the dis-placement of the rain field due to the movement of air masses, while the rain intensity along the receiving path is estimated by the attenuation of the radio signal between the satellite and the ground receiver. To realize the proposed system, a complete receiver setup and an existing, operational group of satellites are selected. A widely known rain field modeling method is applied to generate test data and evaluate the system. The feasibility of a technically realizable system is provided, and its capabilities are compared with a hypothetical, ideal system. The methods and algorithms are tested on an existing geographical location, simulating a real operating environment.

Boundary-Free Analytic Magnetic Field Calculations Including Soft Iron and Permanent Magnets Using an Iterative Discretization Technique

An extremely fast magnetostatic magnetic field modeling method is developed that includes nonlinear relative permeabilities (or “magnetic saturation”) of soft magnetic materials with nonuniform magnetization. The model assumes regions of linearity within the material in order to apply analytic equations and superposition. This article presents the general theory and method for 3-D geometries, along with a 2-D axisymmetric example case study that is of interest for tubular linear actuator (or motor) design. The case study maximizes the average air-gap flux of an axially magnetized pole piece and shows a close correlation of the internal and external magnetic flux densities with a finite element analysis. This demonstrates the method as suitable for large parametric searches of topologies, toward the optimization of electrical machines, linear actuators, transformers, or more general 3-D electromagnetic problems.

A review on the applications of the chemical reactor network approach on the prediction of pollutant emissions

PurposeThe purpose of this paper is to review the applications of the chemical reactor network (CRN) approach for modeling the combustion in gas turbine combustors and classify the CRN construction methods that have been frequently used by researchers.Design/methodology/approachThis paper initiates with introducing the CRN approach as a practical tool for precisely predicting the species concentrations in the combustion process with lower computational costs. The structure of the CRN and its elements as the ideal reactors are reviewed in recent studies. Flow field modeling has been identified as the most important input for constructing the CRNs; thus, the flow field modeling methods have been extensively reviewed in previous studies. Network approach, component modeling approach and computational fluid dynamics (CFD), as the main flow field modeling methods, are investigated with a focus on the CRN applications. Then, the CRN construction approaches are reviewed and categorized based on extracting the flow field required data. Finally, the most used kinetics and CRN solvers are reviewed and reported in this paper.FindingsIt is concluded that the CRN approach can be a useful tool in the entire process of combustion chamber design. One-dimensional and quasi-dimensional methods of flow field modeling are used in the construction of the simple CRNs without detailed geometry data. This approach requires fewer requirements and is used in the initial combustor designing process. In recent years, using the CFD approach in the construction of CRNs has been increased. The flow field results of the CFD codes processed to create the homogeneous regions based on construction criteria. Over the past years, several practical algorithms have been proposed to automatically extract reactor networks from CFD results. These algorithms have been developed to identify homogeneous regions with a high resolution based on the splitting criteria.Originality/valueThis paper reviews the various flow modeling methods used in the construction of the CRNs, along with an overview of the studies carried out in this field. Also, the usual approaches for creating a CRN and the most significant achievements in this field are addressed in detail.

Proposal of field modeling method and seamlessization to terramechanics analysis

Proposal of field modeling method and seamlessization to terramechanics analysis

Efficient gravity field modeling method for small bodies based on Gaussian process regression

The detection of small bodies is very important, and studying the gravity fields of small bodies is a key requirement when designing exploration missions. This paper proposes an efficient gravity field modeling method based on Gaussian process regression from the novel perspective of data statistical and law mining. In contrast to classical gravity field modeling methods, the proposed method establishes a direct mapping relationship between the gravity field and the field point from a statistical point of view, which avoids the complex modeling calculation process. This method can accurately obtain the gravitational acceleration at a checkpoint while improving the calculation efficiency. In order to ensure the quality of the data samples required for the Gaussian process regression, a training set is obtained using a high-precision polyhedron modeling method. The kernel functions are selected, and the hyperparameters are optimized to establish a gravity field training model. Numerical simulations demonstrated that the mean relative error was only 1.27% when this approach was applied to the nearby gravity field modeling of four target small bodies with different sizes. In terms of the runtime requirements, the magnitude of computing time was reduced from 104 s for the polyhedron method to 10−1 s.

Computational Study of Single Droplet Deposition on Randomly Rough Surfaces: Surface Morphological Effect on Droplet Impact Dynamics

Tremendous efforts have been devoted to the modeling of droplet deposition on smooth and patterned surfaces with ordered structures. However, systematic work focusing on randomly rough surfaces, which are the most common bare substrate surfaces, can be hardly identified. A phase field modeling method together with a unique analysis approach has been developed in this work to characterize single droplet deposition on randomly rough surfaces. It is interesting to observe that the droplet shape evolves quite differently on a randomly rough surface, as compared to a patterned surface, even if two surfaces have the same roughness. Parametric studies have been carried out to explore how the morphological metrics of randomly rough surfaces, which include the Wenzel roughness parameter (Wr) and the root-mean-square roughness (Rr), can affect droplet impact dynamics. The quantitative relationships derived from this study can eventually shed light on droplet shape on-aim control during the deposition process, which...

Analisa stabilitas struktur revetmen di Pantai Kedungu, Tabanan Bali

Study in Kedungu Beach which has a wide sand dunes and dense vegetation. This place is usually used for tourism by local residents. Causes of erosion is awave come in the form an angle, create longshore current, and litoral drif sediments. The condition is very alarming, because it erodes the amount of land owned by residents. Until now there is no goverment handling yet, only the efforts of the local community by building sea walls and currently also not in a proper condition. Based on the analysis of the data captured in the field and numerical modeling methods, resulting the methode to overcome the erotion problem, i.e. build coastal protection structures such as revetment, where the structure serves as an incoming wave damper and defend the coastline. The purpose of this paper is to provide an overview of the structure stability of revetment against coastal erosion.Stability analysis takes into account the stability of the rolling, sliding, and soil bearing capacity decrease. The dimension and design ofrevetment is secure from overturning (SF = 7.669 > 2); sliding (SF = 4.082>1,5) and bearing capacity support (17.498>3). From this analysis concluded that in the revetment structure design safe and can be applied in the study area. Analysis of the stability of the revetment structure is expected to reduce the level of damage to the building structure coast and surrounding buildings.

Long-term knowledge evolution modeling for empirical engineering knowledge

In this era of knowledge economy, appropriate management of the rapidly evolving knowledge is a real and urgent issue for factories and enterprises, in order to maintain the competitive edges. However, facing the onerous analysis required for understanding the long-term knowledge evolution, especially the evolving of empirical knowledge in the engineering field, effective and comprehensive modeling methods for knowledge evolution are absent. In this paper, a novel knowledge evolution modeling method is proposed for portraying the long-term evolution of empirical engineering knowledge (EEK) and assisting engineers in comprehending the evolving history. Three phases, EEK elicitation and formalization, EEK networks foundation, and family-tree evolution model construction, are included in the modeling method. This method is developed using natural language processing, semantic similarity calculation, fuzzy neural network prediction, clustering algorithm, and latent topic extraction techniques. To evaluate the performance of the proposed modeling method, an evolution model of empirical knowledge in computer-aided design (CAD) is constructed and then verified. Experimental results show that the proposed method outperforms the former approaches in feasibility and effectiveness, and hence opens up a better way of further understanding the long-term evolution course of EEK.

The Electromagnetic Transient Model for High-Speed Railway Viaducts Struck by Lightning Based on the Decoupling Method

The overhead catenary system of high-speed railway, usually supported by viaducts, attracts more direct strikes than the conventional railway. However, there are ten thousands of slender steel rods in the reinforced concrete structure of viaducts. Therefore, it takes a lot of time to calculate the model of a long series of viaducts by the conventional electromagnetic field modeling method. An electromagnetic transient model for high-speed railway viaducts struck by lightning based on the decoupling method is proposed in this paper, in which the railway viaducts are divided into the box girder unit and viaduct pier unit. The viaducts model based on decoupling method (VMDM) is established by a series of box units supported by viaduct pier units at equal intervals. The equivalent circuit model of each unit was obtained by employing the vector fitting method based on the frequency-domain response. Experimental results of a newly built railway viaduct pier under lightning impulse current were presented to validate the equivalent circuit model of viaduct pier unit, which show high consistency with simulation results. In particular, the typical VMDM model of Beijing-Tianjin intercity railway viaducts was established with the proposed method. The result obtained from the VMDM model are compared with the simplified model.

Stochastic simulation and analysis of geological corrosion defects in dam foundation

Uncertainty in geological structural modeling, especially geological corrosion(a kind of karst cave), is a bottleneck that restricts the development and application of geological computer modeling and effect estimation. To solve this issue, a stochastic modeling method based on the random field theory is proposed in comparison with the deterministic geometric modeling method. Then the constraint random field modeling method and the random field modeling method without constrained parameters are compared and analyzed. A case study shows that the novel stochastic simulation method is an effective tool to describe the distribution characteristics of corrosion parameters and reflect the updated geological prospecting information. The influence of geological corrosion on the dam behavior can also be better analyzed by using the stochastic simulation method. At the same time, the unconfined random field ignores the sample location information and may lead to higher variability. Therefore, the constraint random field modeling method can provide a useful reference for the numerical analysis under complex geological conditions.

A multiscale approach to determine hydraulic conductivity in thick claystone aquitards using field, laboratory, and numerical modeling methods

AbstractCharacterizing the hydraulic conductivity (K) of aquitards is difficult due to technical and logistical difficulties associated with field‐based methods as well as the cost and challenge of collecting representative and competent core samples for laboratory analysis. The objective of this study was to produce a multiscale comparison of vertical and horizontal hydraulic conductivity (Kv and Kh, respectively) of a regionally extensive Cretaceous clay‐rich aquitard in southern Saskatchewan. Ten vibrating wire pressure transducers were lowered into place at depths between 25 and 325 m, then the annular was space was filled with a cement‐bentonite grout. The in situ Kh was estimated at the location of each transducer by simulating the early‐time pore pressure measurements following setting of the grout using a 2‐D axisymmetric, finite element, numerical model. Core samples were collected during drilling for conventional laboratory testing for Kv to compare with the transducer‐determined in situ Kh. Results highlight the importance of scale and consideration of the presence of possible secondary features (e.g., fractures) in the aquitard. The proximity of the transducers to an active potash mine (∼1 km) where depressurization of an underlying aquifer resulted in drawdown through the aquitard provided a unique opportunity to model the current hydraulic head profile using both the Kh and Kv estimates. Results indicate that the transducer‐determined Kh estimates would allow for the development of the current hydraulic head distribution, and that simulating the pore pressure recovery can be used to estimate moderately low in situ Kh (<10−11 m s−1).

Coil Magnetic Field Modeling in 3-D Space

Problem of modeling of magnetic field created by coils with or without cores in 3-D space using finite element method isinvestigated. Created overall modeling algorithm is presented and magnetic field modeling method in 3-D space was proposed.Problems of coil and core construction library creation are investigated. Questions concerning application of different type finiteelements in creation of coil construction models and description of core and other regions of model are analyzed. Finite element meshcreation is discussed. Example of modeling of magnetic field created by coil with core is presented. Ill.9, bibl.5 (in English; summariesin Lithuanian, English and Russian).

Random field modeling with insufficient field data for probability analysis and design

Often engineered systems entail randomness as a function of spatial (or temporal) variables. The random field can be found in the form of geometry, material property, and/or loading in engineering products and processes. In some applications, consideration of the random field is a key to accurately predict variability in system performances. However, existing methods for random field modeling are limited for practical use because they require sufficient field data. This paper thus proposes a new random field modeling method using a Bayesian Copula that facilitates the random field modeling with insufficient field data and applies this method for engineering probability analysis and robust design optimization. The proposed method is composed of three key ideas: (i) determining the marginal distribution of random field realizations at each measurement location, (ii) determining optimal Copulas to model statistical dependence of the field realizations at different measurement locations, and (iii) modeling a joint probability density function of the random field. A mathematical problem was first employed for the purpose of demonstrating the accuracy of the random field modeling with insufficient field data. The second case study deals with the assembly process of a two-door refrigerator that challenges predicting the door assembly tolerance and minimizing the tolerance by designing the random field and parameter variables in the assembly process with insufficient random field data. It is concluded that the proposed random field modeling can be used to successfully conduct the probability analysis and robust design optimization with insufficient random field data.

Methods of Handling the Aliasing and Tolerance Problem for a New Unified Fault Modeling Technique in Analog-Circuit Fault Diagnosis

Soft fault diagnosis and tolerance are two challenging problems in analog circuit fault diagnosis. This paper proposes approaches to solve these two problems. First, a complex field modeling method and its theoretical proof are presented. This fault modeling method is applicable to both hard (open or short) and soft (parametric) faults. It is also applicable to either linear or nonlinear analog circuits. Then, the parameter tolerance is taken into consideration. A frequency selection method is proposed to maximize the difference between the faults fault signature. Hence, the aliasing problem arise from tolerance can be mitigated. The effectiveness of the proposed approaches is verified by simulated results.

Complex Field Fault Modeling-Based Optimal Frequency Selection in Linear Analog Circuit Fault Diagnosis

Owing to the lack of feasible fault modeling method, hard (open and short) faults, and discretized parametric faults are still the mostly used fault models. These models cannot characterize all soft (parameter shifting) faults because that the parameter of analog element be of continuity character. To address this concern, a complex field fault modeling method is presented first. If fault happens to passive element xi in linear analog circuit, the real (Ur) and imaginary (Uj) parts of faulty voltage phasor U°(U°=Ur+j Uj) must satisfy binary quadratic function Fi(Ur,Uj)=0, which is independent from the value of element xi and uniquely determined by its location and the nominal circuit under test. Hence, the binary quadratic function can model any continuous parameter shifting (soft) or hard fault. Second, to avoid calculating the explicit expression of binary quadratic function, a simulation-based method is given to obtain the locus of the change in the function Fz in the complex plane. Besides, the nominal (fault-free) point, the loci determined by the binary quadratic functions might intersect with each other. It is referred to as aliasing problem in this paper. This problem can be solved by adjusting the frequency of the input signal. Therefore, a constraint optimization method is proposed to select optimal test frequencies. The proposed test generation and compression methods, when combined with the complex field modeling method, can pinpoint much more fault components with less test points and frequencies when compared with the other methods.