Refinement Strategy Research Articles

Corrosion behavior of an ultrafine-grained Ti6Al4V-5Cu alloy in artificial saliva containing fluoride ions

Ti6Al4V alloy has been widely used in dental applications, such as orthodontic mini-implants. However, it has been reported that fluoride ions could obviously accelerate the corrosion of implant materials and affect their performance. This work aimed to improve the F− erosion resistance of Ti6Al4V alloy through the strategy of both Cu addition and grain refinement. As contrasted with Ti6Al4V alloy, both the coarse- and ultrafine-grained Ti6Al4V-5Cu alloys effectively mitigated the acceleration of the fluoride ions to the anode process, because Cu substituents blocked the continuous damage of FO· doped in the passive film. Furthermore, grain refinement enhanced the protective ability of the passive film, more oxides and less adsorption amount of fluorides presented in the passive film of ultrafine-grained Ti6Al4V-5Cu alloy than those of coarse-grained Ti6Al4V-5Cu alloy. Under the combination of Cu alloying and grain refinement, the ultrafine-grained Ti6Al4V-5Cu alloy is greatly appropriate for the fabrication of orthodontic devices.

Multiscale modeling on the multi-physical behaviors of high temperature superconducting magnets based on a combined global homogenization and local refinement scheme

The safe and stable operation is a crucial issue in the development of high-field high temperature superconducting (HTS) magnets. In this paper, we construct a multiscale model which couples the homogenized global (macroscopic) behavior and the refined local (mesoscopic) characteristics to simulate the coupled electromagnetic-mechanical-thermal behaviors of the HTS magnets. In the model, the numerical homogenization method is adopted to simulate the macroscopic behavior of the magnets and identify the ‘dangerous region’ of the magnet which are prone to damage or quench. Then, a refined local sub-model which coupling with the macroscopic homogenization model is established by considering the microstructure and physical parameters of each components of the HTS tapes in the ‘dangerous region’. Thus, a combined global homogenization and local refinement scheme which balances the computational efficiency and numerical accuracy is developed to simulate the coupled multi-physical behaviors of the HTS magnets including the quench and its propagation. Our results show that the refined local sub-model can simulate the electromagnetic field and the stress-strain at the scale of the tape more accurately. Characteristics, such as the discontinuous stress distribution across the interfaces between different layers and the current shunt from the HTS layer to metallic layers during the quench process of HTS tapes, which are beyond the capability of the homogenization model, have also been well depicted by the refined sub-model.

A Delaunay refinement algorithm for the particle finite element method applied to free surface flows

AbstractThis article proposes two contributions to the calculation of free‐surface flows using the particle finite element method (PFEM). The PFEM is based upon a Lagrangian approach: a set of particles defines the fluid and each particle is associated with a velocity vector. Then, unlike a pure Lagrangian method, all the particles are connected by a triangular mesh. The difficulty lies in locating the free surface from this mesh. It is a matter of deciding which of the elements in the mesh are part of the fluid domain, and to define a boundary—the free surface. Then, the incompressible Navier–Stokes equations are solved on the fluid domain and the particle position is updated using the velocity vector from the finite element solver. Our first contribution is to propose an approach to adapt the mesh with theoretical guarantees of quality: the mesh generation community has acquired a lot of experience and understanding about mesh adaptation approaches with guarantees of quality on the final mesh. The approach we use here is based on a Delaunay refinement strategy, allowing to insert and remove nodes while gradually improving mesh quality. We show that what is proposed allows to create stable and smooth free surface geometries. One characteristic of the PFEM is that only one fluid domain is modeled, even if its shape and topology change. It is nevertheless necessary to apply conditions on the domain boundaries. When a boundary is a free surface, the flow on the other side is not modeled, it is represented by an external pressure. On the external free surface boundary, atmospheric pressure can be imposed. Nevertheless, there may be internal free surfaces: the fluid can fully encapsulate cavities to form bubbles. The pressure required to maintain the volume of those bubbles is a priori unknown. For example, the atmospheric pressure would not be sufficient to prevent the bubbles from deflating and eventually disappearing. Our second contribution is to propose a multi‐point constraint approach to enforce global incompressibility of those empty bubbles. We show that this approach allows to accurately model bubbly flows that involve two fluids with large density differences, for instance water and air, while only modeling the heavier fluid.

Stray light analysis and suppression of high-resolution camera line-of-sight variation real-time monitoring system (LoS Var RTMS).

Due to environmental disturbances during emission and operation processes, the line-of-sight of a high-resolution camera is highly prone to variation, resulting in a significant decrease in image positioning accuracy. To address this issue, we propose a line-of-sight variation real-time monitoring system (LoS Var RTMS). A full-link active optical monitoring system is established using laser, and a high-resolution camera is coupled to a star tracker, thereby enhancing the on-orbit calibration and image positioning accuracy of the camera. However, the high-resolution camera LoS Var RTMS belongs to a high stray light sensitivity system. Stray light entering the star tracker from the high-resolution camera through the relay reflective system can significantly affect the imaging of the star tracker, leading to the failure of the monitoring system. Therefore, a comprehensive and accurate analysis of the stray light propagation path in the monitoring system is necessary to ensure its normal operation. In response to this issue, this article proposes a stray light analysis method based on the surface subdivision method, and utilizes inverse ray tracing to meticulously analyze the propagation path of stray light. Additionally, to address the impact of stray light on laser light in the LoS Var RTMS, an inner baffle polarization filtering system is designed to effectively suppress the influence of external strong stray light on the monitoring system. The results demonstrate that the stray light analysis method based on the surface subdivision method not only enhances the integrity and accuracy of the analysis of stray light propagation paths within the monitoring system, but also significantly improves the precision of stray light analysis. It provides a reference for the analysis of stray light in high stray light sensitive systems. Moreover, the design of the inner baffle polarization filtering system effectively distinguishes between lasers and stray light, suppressing stray light within the high-resolution camera LoS Var RTMS and ensuring its normal operation.

A [formula omitted] continuous multi-patch framework for adaptive isogeometric topology optimization of plate structures

This study proposes a novel computationally efficient methodology to perform topology optimization (TO) of fourth-order plate structures within the framework of multi-patch isogeometric analysis. This is realized by taking the multifold benefits of isogeometric PHT-Splines to (1) discretize the C1 continuous weak form of plate structures, (2) develop a C0 continuous density field for the material distribution in TO and inherently remove the need for filters, and (3) provide a hierarchical tree structure for the structural mesh to effortlessly implement an adaptive mesh refinement (AMR) strategy. Moreover, to ensure continuity between isogeometric patches, we adopt a strong C1 coupling between the boundaries. This is established by constructing new basis functions, defined as a linear combination of existing C0 functions at the patch interfaces. The density field in TO is further enhanced with a first-neighbourhood smoothening algorithm based on the Shepard function to generate printable topologies and alleviate the post-processing stages after optimization. An element-centre density, based on the control point densities of the isogeometric mesh, is used as the marking scheme for the AMR to determine the subdomains to be refined. Utilizing the Geometry Independent Field approximaTion, the design and adaptive analysis-optimization stages were independently discretized respectively through NURBS and PHT-Splines, allowing easy transfer of multi-patch geometries from industry-standard packages. Multiple numerical examples illustrate the stability of the multi-patch algorithm in optimizing the geometries effectively. The results also show considerable advantages in terms of solution accuracy such as precise field, smooth topology and computational efficiency.

Numerical simulation analysis of slope stability from rainwater utilizing the Civil3D+Flac3D coupling

Building Information Modeling (BIM) technology serves as an effective means for engineering modeling and information integration, surpassing traditional two-dimensional approaches with its superior spatial analysis capabilities. While BIM has gained widespread applications in slope engineering, a gap persists in the integration between protective design and simulation analysis in terms of slope stability. This study employs literature review, theoretical analysis, software development, and numerical simulation methods to explore the application of BIM models in slope stability analysis. Through the integrated application of BIM model construction, mesh subdivision, and stability analysis, we address the deficiency in three-dimensional slope stability inherent in BIM by coupling Civil3D’s secondary development with Flac3D, a numerical simulation software. This approach not only addresses the shortcomings of numerical analysis software in constructing complex geological models but also employs a collaborative multi-software approach for comparison to validate its suitability in slope engineering. The results demonstrate that models built using BIM software are more comprehensive and possess high precision in numerical simulation, thus exhibiting significant practical value in real-world engineering applications.

Eating and Cognition in Two Animals without Neurons: Sponges and Trichoplax

AbstractEating is a fundamental behavior in which all organisms must engage in order to procure the material and energy from their environment that they need to maintain themselves. Since controlling eating requires procuring, processing, and assessing information, it constitutes a cognitive activity that provides a productive domain for pursuing cognitive biology as proposed by Ladislav Kováč. In agreement with Kováč, we argue that cognition is fundamentally grounded in chemical signaling and processing. To support this thesis, we adopt Cisek’s strategy of phylogenetic refinement, focusing on two animal phyla, Porifera and Placozoa, organisms that do not have neurons, muscles, or an alimentary canal, but nonetheless need to coordinate the activity of cells of multiple types in order to eat. We review what research has revealed so far about how these animals gather and process information to control their eating behavior.

Lagrangian relaxation for continuous‐time optimal control of coupled hydrothermal power systems including storage capacity and a cascade of hydropower systems with time delays

AbstractThis work considers a short‐term, continuous time setting characterized by a coupled power supply system controlled exclusively by a single provider and comprising a cascade of hydropower systems (dams), fossil fuel power stations, and a storage capacity modeled by a single large battery. Cascaded hydropower generators introduce time‐delay effects in the state dynamics, which are modeled with differential equations, making it impossible to use classical dynamic programming. We address this issue by introducing a novel Lagrangian relaxation technique over continuous‐time constraints, constructing a nearly optimal policy efficiently. This approach yields a convex, nonsmooth optimization dual problem to recover the optimal Lagrangian multipliers, which is numerically solved using a limited memory bundle method. At each step of the dual optimization, we need to solve an optimization subproblem. Given the current values of the Lagrangian multipliers, the time delays are no longer active, and we can solve a corresponding nonlinear Hamilton–Jacobi–Bellman (HJB) Partial Differential Equation (PDE) for the optimization subproblem. The HJB PDE solver provides both the current value of the dual function and its subgradient, and is trivially parallelizable over the state space for each time step. To handle the infinite‐dimensional nature of the Lagrange multipliers, we design an adaptive refinement strategy to control the duality gap. Furthermore, we use a penalization technique for the constructed admissible primal solution to smooth the controls while achieving a sufficiently small duality gap. Numerical results based on the Uruguayan power system demonstrate the efficiency of the proposed mathematical models and numerical approach.

Research on the Ghost Cell Immersed Boundary Method for Compressible Flow

In this paper, a kind of immersed boundary method, the discretized force with ghost cell method, is introduced to study compressible flow. Meanwhile, an adaptive mesh refinement scheme and a wall treatment for turbulent flow are proposed. With the help of in-house code, the accuracy of the method is verified based on several classic tests.

GlyReShot: A glyph-aware model with label refinement for few-shot Chinese agricultural named entity recognition

Chinese agricultural named entity recognition (NER) has been studied with supervised learning for many years. However, considering the scarcity of public datasets in the agricultural domain, exploring this task in the few-shot scenario is more practical for real-world demands. In this paper, we propose a novel model named GlyReShot, integrating the knowledge of Chinese character glyph into few-shot NER models. Although the utilization of glyph has been proven successful in supervised models, two challenges still persist in the few-shot setting, i.e., how to obtain glyph representations and when to integrate them into the few-shot model. GlyReShot handles the two challenges by introducing a lightweight glyph representation obtaining module and a training-free label refinement strategy. Specifically, the glyph representations are generated based on the descriptive sentences by filling the predefined template. As most steps come before training, this module aligns well with the few-shot setting. Furthermore, by computing the confidence values for draft predictions, the refinement strategy selectively utilizes the glyph information only when the confidence values are relatively low, thus mitigating the influence of noise. Finally, we annotate a new agricultural NER dataset and the experimental results demonstrate effectiveness of GlyReShot for few-shot Chinese agricultural NER.

An enhanced compressible two-phase flow model with detailed chemistry under the adaptive mesh refinement frame

In the present study, an enhanced compressible two-phase flow model is advanced, considering the effect of chemical reactions within a detailed mechanism. In this model, two immiscible fluids (liquid and gaseous mixture) are accurately separated with the resolved interface. Unlike the classical five-equation two-phase flow model, the thermal properties of gases are no longer assumed to be constant but rather vary as functions of temperature. A modified mechanical relaxation procedure is proposed and employed at the gas-liquid interface to prevent the occurrence of nonphysical pressure oscillation. In the gaseous mixture, numerous gas components are included and resolved by their mass fraction among the gaseous mixture. In this model, the heat release effect is simulated by a detailed chemistry. Furthermore, the numerical results of several benchmark problems in one dimension and two dimensions demonstrate the efficacy of the proposed compressible multiphase flow model, such as the air shock tube, the gaseous detonation tube, the shock-droplet interaction, and especially the detonation-droplet interaction that has received little focused interest and investigations. Moreover, a self-developed adaptive mesh refinement strategy is performed for a high efficiency of numerical solving.

Simulation of coupled elasticity problem with pressure equation: hydroelastic equation

PurposeThe main aim of the current paper is to find a numerical plan for hydraulic fracturing problem with application in extracting natural gases and oil.Design/methodology/approach First, time discretization is accomplished via Crank-Nicolson and semi-implicit techniques. At the second step, a high-order finite element method using quadratic triangular elements is proposed to derive the spatial discretization. The efficiency and time consuming of both obtained schemes will be investigated. In addition to the popular uniform mesh refinement strategy, an adaptive mesh refinement strategy will be employed to reduce computational costs.FindingsNumerical results show a good agreement between the two schemes as well as the efficiency of the employed techniques to capture acceptable patterns of the model. In central single-crack mode, the experimental results demonstrate that maximal values of displacements in x- and y- directions are 0.1 and 0.08, respectively. They occur around both ends of the line and sides directly next to the line where pressure takes impact. Moreover, the pressure of injected fluid almost gained its initial value, i.e. 3,000 inside and close to the notch. Further, the results for non-central single-crack mode and bifurcated crack mode are depicted. In central single-crack mode and square computational area with a uniform mesh, computational times corresponding to the numerical schemes based on the high order finite element method for spatial discretization and Crank-Nicolson as well as semi-implicit techniques for temporal discretizations are 207.19s and 97.47s, respectively, with 2,048 elements, final time T = 0.2 and time step size τ = 0.01. Also, the simulations effectively illustrate a further decrease in computational time when the method is equipped with an adaptive mesh refinement strategy. The computational cost is reduced to 4.23s when the governed model is solved with the numerical scheme based on the adaptive high order finite element method and semi-implicit technique for spatial and temporal discretizations, respectively. Similarly, in other samples, the reduction of computational cost has been shown.Originality/valueThis is the first time that the high-order finite element method is employed to solve the model investigated in the current paper.

Efficient Refinement of Complex Structures of Flexible Histone Peptides Using Post-Docking Molecular Dynamics Protocols.

Histones are keys to many epigenetic events and their complexes have therapeutic and diagnostic importance. The determination of the structures of histone complexes is fundamental in the design of new drugs. Computational molecular docking is widely used for the prediction of target-ligand complexes. Large, linear peptides like the tail regions of histones are challenging ligands for docking due to their large conformational flexibility, extensive hydration, and weak interactions with the shallow binding pockets of their reader proteins. Thus, fast docking methods often fail to produce complex structures of such peptide ligands at a level appropriate for drug design. To address this challenge, and improve the structural quality of the docked complexes, post-docking refinement has been applied using various molecular dynamics (MD) approaches. However, a final consensus has not been reached on the desired MD refinement protocol. In this present study, MD refinement strategies were systematically explored on a set of problematic complexes of histone peptide ligands with relatively large errors in their docked geometries. Six protocols were compared that differ in their MD simulation parameters. In all cases, pre-MD hydration of the complex interface regions was applied to avoid the unwanted presence of empty cavities. The best-performing protocol achieved a median of 32% improvement over the docked structures in terms of the change in root mean squared deviations from the experimental references. The influence of structural factors and explicit hydration on the performance of post-docking MD refinements are also discussed to help with their implementation in future methods and applications.

Geometric Modelling of a Family of 4-Point Ternary Approximating Subdivision Scheme U_φ with Visual Performance

Making signals better than noise in communication has always been challenging for scientists. Researchers have been working on it in different ways. The computer-aided geometric design is a new research field emerging from the collaboration of computer algorithms and mathematical logic towards curve designing, in which the subdivision schemes used have a key position due to their flexible and smooth behaviour. Using parameters in these schemes allows for increased control over designing. A parameterized framework for generating a wide range of subdivision surfaces with tunable degrees of shape control is presented in the family of schemes. The properties of the proposed family make it suitable for use in isogeometric analysis, computer animation, and geometric modelling. The purpose of this paper is to construct and analyze a family of 4-point ternary subdivision schemes to smooth the curves based on the Laurant polynomial. This family is generated by tuning the weight parameter. The scheme is analysed for its different properties. The scheme has continuity. Visual performance of the subdivision scheme is also provided as an application of this proposed study.

Refining the reconstruction-based Monte Carlo methods for solving breakage population balance equation

This work presents a class of refinement reconstruction-based Monte Carlo methods dedicated to solving a generic breakage population balance equation. The focus is on enhancing the precision and computational speed of the existing reconstruction scheme by incorporating two refinement strategies, including effective-breakage ratios and population scaling rules with local coarsening/refinement based on adaptive subdomain meshes. A comparative analysis of the performances of the proposed methods is conducted for the benchmark breakage case with a known analytical solution. The results indicate that the accuracy can be significantly increased by a stepwise-varying breakage ratio and the local refinement scaling rule, whereas the cost can be reduced by properly tuning parameters related to the refinement strategies. In addition, multi-objective optimization is introduced to achieve optimal simulation with the least systematic and statistical errors and CPU time, offering further insights into the combination of conditions required for the Monte Carlo methods to yield the best possible efficiency.

Exploring energy selection methods for robust biologically optimized carbon ion arc for head&neck cancer patients

BackgroundDue to the advantageous depth dose profile of carbon ion beams, carbon ion therapy is commonly applied in the form of intensity modulated particle therapy (IMPT) with few treatment fields. Carbon ion arc therapy (C-Arc) has recently been proposed to improve dose conformity and increase the dose-averaged linear energy transfer (LETd) inside the target to levels relevant for overcoming tumor radioresistance. In this work, we investigate different energy selection approaches for C-Arc, including a novel greedy energy layer refinement strategy.MethodsRobust biologically optimized C-Arc plans were generated for six head &neck cancer patient previously treated at the Shanghai Proton and Heavy Ion Center (SPHIC). Different heuristic approaches for mono- and dual-energy C-Arc were implemented, and compared to carbon IMPT pans. A novel greedy energy layer refinement was developed, acting directly on the dose influence matrix, rather than on an iterative plan optimization. A key challenge in C-Arc with few energy layers per angle is the sharpness of the carbon ion Bragg peak, which is challenging for plan robustness. To improve robustness and plan quality, we propose the use of a 6 mm ripple filter instead of the typical 3 mm ripple filter used for carbon IMPT.ResultsMost mono-energetic C-Arc plans were able to meet the established clinical goals, but some of the heuristic energy selection schemes were not universally applicable with low plan quality in some patients. The developed energy layer refinement strategy delivered high quality plans even for complex cases. Mono-energetic C-Arc plans presented an average increase between 10% and 33% in the maximum LETd in the target, with similar or up to 19% improved average target LETd50%\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$_{50\\%}$$\\end{document} compared to the IMPT carbon ion plans. C-Arc plans with 2 energies per treatment angle, for the employed energy selection heuristic, improved dosimetric quality compared to mono-energetic C-Arc plans, but did not provide the same natural improvement in LETd compared to IMPT.ConclusionsFor small, centrally located targets C-Arc demonstrates the greatest potential, but feasible plans could also be achieved for more complex cases in this work. Further development is necessary for improving C-Arc delivery efficiency and plan quality toward possible clinical application.

A phase field approach to the fracture simulation of quasi-brittle structures with initial state

To solve the simulation problem of crack propagation in solid structures with initial stress, this paper proposes a phase field approach that considers the initial state of the quasi-brittle structure. By using the initial equilibrium iteration method, the estimated initial state of the structure, including initial stress, is transformed into internal stress loads of the structure. Thus, the problem of non-convergence caused by inaccurate initial state estimation of the structure in engineering calculations was solved, and an improved subproblem staggered iteration method was adopted to simulate crack propagation of the structure under external loads. The universality and computational accuracy of this method for different phase field models were verified by using pre made notched thin plates for the expansion of mode I and II cracks in different initial states. Among them, the calculation error using the PF_CZM model is within 1%, and the calculation error of the AT2 model increases with the initial stress, but is less than 7%. At the same time, the crack growth problem of cracked structures under different uniform initial stresses is accurately simulated, which reflects the applicability of this method to actual engineering. In addition, the study also verified the universal applicability of the adaptive refinement strategy proposed based on the AT2 model for other phase field models.

An enhanced direct position determination of non-circular sources via sparse Bayesian inference and grid refinement strategy

In this study, an off-grid sparse Bayesian inference (OGSBI) based direct position determination (DPD) algorithm is investigated. Existing SBI-based DPD algorithms are confronted with the challenge of excessive computational loads and lack of consideration for non-circular (NC) signals. To address these limitations, we present an enhanced OGSBI-based DPD algorithm for multiple non-circular sources. By utilizing the conjugate information of the NC signals, we expand the dimensionality of the data matrix to achieve a significant improvement in the localization performance. Additionally, a grid refinement strategy is developed to alleviate the computational loads, which involves an initial search to determine the approximate source locations, followed by fine localization using a denser grid. Moreover, the computational complexity and Cramér-Rao lower bound are derived to provide a comprehensive analysis of the proposed algorithm. Numerical simulations demonstrate the superiority of the proposed algorithm in terms of both localization accuracy and computational efficiency.

The adaptive hygrothermo–magneto–electro–elastic coupling improved enriched finite element method for functionally graded magneto–electro–elastic structures

In this study, the hygrothermo–magneto–electro–elastic coupling improved enriched finite element method (HC-IEFEM) is proposed to analyze functionally graded magneto–electro–elastic (FG-MEE) structures. The static behavior of FG-MEE structures in the hygrothermal environment is studied. In the enriched finite element method (EFEM) enhanced by interpolation cover functions, the improved shape functions are added to solve the rank defect problem. Quadrilateral elements are used in the analysis of FG-MEE structures in this study. This improved method has proven to be relatively more efficient and resistant to mesh distortion than the traditional finite element method (FEM). Besides, the adaptive mesh refinement (AMR) scheme is used to refine the mesh in local areas to improve numerical calculation efficiency. Numerical examples show that the adaptive HC-IEFEM can achieve relatively high accuracy for analyzing FG-MEE structures. The proposed HC-IEFEM can obtain high accuracy in the hygrothermal environment using a relatively coarse mesh through the improved shape function and AMR scheme. Therefore, the significant potential is demonstrated in analyzing FG-MEE structures in the hygrothermal environment using the proposed adaptive HC-IEFEM.

TSAR-MVS: Textureless-aware segmentation and correlative refinement guided multi-view stereo

The reconstruction of textureless areas has long been a challenging problem in MVS due to lack of reliable pixel correspondences between images. In this paper, we propose the Textureless-aware Segmentation And Correlative Refinement guided Multi-View Stereo (TSAR-MVS), a novel method that effectively tackles challenges posed by textureless areas in 3D reconstruction through filtering, refinement and segmentation. First, we implement the joint hypothesis filtering, a technique that merges a confidence estimator with a disparity discontinuity detector to eliminate incorrect depth estimations. Second, to spread the pixels with confident depth, we introduce an iterative correlation refinement strategy that leverages RANSAC to generate 3D planes based on superpixels, succeeded by a weighted median filter for broadening the influence of accurately determined pixels. Finally, we present a textureless-aware segmentation method that leverages edge detection and line detection for accurately identify large textureless regions for further depth completion. Experiments on ETH3D, Tanks & Temples and Strecha datasets demonstrate the superior performance and strong generalization capability of our proposed method.