Boundary Reconstruction Research Articles

A Field Experiment for Tracing Lateral Subsurface Flow in a Post-Glacial Hummocky Arable Soil Landscape

Lateral subsurface flow (LSF) is a phenomenon that is widely occurring including the hummocky ground moraine landscape. Due to the heterogeneous structure of the subsurface, transport times of pesticides and nutrients from agricultural areas to adjacent water bodies are difficult to assess. Here, LSF at Luvisol and Regosol plots of an experimental field were studied by applying potassium bromide along a 10 m trench below the plow pan in October 2019. The soil solution was collected in suction cups 3 m downslope of the trench and in April 2021, the soil was sampled down to 1 m depth. Almost no bromide was found in the soil solution except for the 160 cm depth of the Regosol plot after a 541 day period. After the same time, bromide was observed in the 90 cm soil depth directly underneath the application trench of the Luvisol plot. A 3D reconstruction of the subsurface horizon boundaries of the Regosol revealed subsurface heterogeneities such as sand lenses that might have been attributed to the heterogeneous subsurface flow pattern.

A defect formation mechanism induced by structural reconstruction of a well-known silicon grain boundary.

Diamond-structured grain boundaries (GBs) are important because they have notable effects on the performances of many functional devices. Previous studies have suggested that the most stable structures of some silicon GBs can be obtained by structural reconstruction from some meta-stable GBs explored at 0 K by atomic simulation. While GB reconstruction is possible to enable these meta-stable GBs to exist at elevated temperatures, reports on such behaviors are rare. This work unveiled a non-reported GB reconstruction from two degenerate ground-states of a well-known silicon GB which can be distinguished by an orientational feature of their unit structures. The reconstructing structures were verified stable by density-functional-theory (DFT) simulation. By thermodynamical and kinetical discussion, we have shown that the structural variation of this well-known GB at elevated temperatures is more likely to be dominated by this reconstruction mechanism rather than by transforming to other metastates. Such a reconstruction mechanism allows the whole GB system to be treated as an Ising model with a second-ordered phase transition. By applying harmonic transition state theory, we predicted the possible concentration of the defects induced by reconstruction at elevated temperatures and discussed their effects on the band structure of the GB by DFT simulation. An explanation was made on the cause of the difference between the phase transition behavior of this silicon GB and that of a reported copper GB. Our research made new insights into understanding the behavior of reconstructing interfaces in covalent-bonded crystalline materials.

Bayesian Method for Inverse Scattering Problem of Interior Cavity with Phaseless Data

This paper is concerned with the inverse acoustic scattering problem of a sound soft cavity based on phaseless near-field data. By combining the reference circle technique with the Bayesian method, this paper presents a numerical algorithm to retrieve the shape of the interior cavity from phaseless data. In this paper, the well-posedness of the Bayesian method is discussed. The posterior distribution of the shape parameters is obtained by DRAM algorithm and the reconstruction of the cavity boundary is acquired by taking the average value of the posterior distribution.

Effect of Er30Cu70 on microstructure and properties of sintered Nd-Fe-B by grain boundary reconstruction

Usually it is generally believed that the Er element forms the Er2Fe14B phase, which will seriously deteriorate the magnetic properties. Distinctly, here we report the balance of corrosion resistance and coercivity in Nd-Fe-B sintered magnets through using simple Er30Cu70 additive whose price is much lower than Dy and Tb. By reasonably controlling Er30Cu70 addition, the corrosion resistance is improved at the minimum limit of reducing the magnetic properties. Through studying the influence mechanism of Er element, it is found that the main effect of Er elements is to replace the Nd elements at the edge of the main phase grains to form a (Er, Nd)2Fe14B shell with low HA, resulting in the reduction of magnetic properties. The improvement of corrosion resistance mainly comes from the more stable Cu element introduced at the grain boundary. At the same time, the target magnets also show different advantages under different heat treatment methods. Above findings may spur progress towards developing the low-cost permanent magnets that rival the commercial Nd-Fe-B counterpart.

Reconstruction of acoustic source with high-curvature part

In this paper, we are concerned with the reconstruction of acoustic sources which contain high-curvature components. We consider the Fourier method developed by Wang X et. al. in [35], and take high-curvature boundary into consideration when choosing Fourier coefficients. We investigate the sophisticated relationship between high frequency Fourier coefficients and high-curvature boundary of the acoustic source, and propose a better cutoff procedure which can greatly enhance the effects in reconstruction of high-curvature boundary. The stability of the proposed method is also derived. Numerical experiments are presented to show the effectiveness of our method. The results may be a new perspective for super-resolution reconstruction of acoustic sources.

Reconstruction of flow domain boundaries from velocity data via multi-step optimization of distributed resistance

Reconstruction of flow domain boundaries from velocity data via multi-step optimization of distributed resistance

Generation of Spatial-Seamless AMSR2 Land Surface Temperature in China During 2012–2020 Using a Deep Neural Network

Land surface temperature (LST) reflects the cold and hot conditions of land surface and is one of the most important geophysical parameters in the study and research of land-atmosphere system. Passive microwave (PMW) is one of the primary techniques for obtaining spatially continuous LST at regional, continental, and global scales. However, there is orbital gap in the LST retrieved from PMW (PMW LST) due to the scanning scheme of PMW sensor, which limits the application of PMW LST, so it is necessary to proposed some methods to fill the orbital gap of PMW LST. In this study, a new orbital gap filling method based on deep neural network (DNN) was developed to address the issue of PMW LST orbital gaps. This method first established DNN model based on the nonlinear relationship between AMSR2 LST and 11 environmental variables, and then used the DNN model to generate a new spatially continuous LST product, namely DNN-LST, and finally used DNN-LST to fill the orbital gaps of AMSR2 LST to generate the daytime/nighttime spatially seamless gap-filled LST product (GF-LST) for China from 2012 to 2020. GF-LST can more correctly represent the spatiotemporal variation of surface temperature in China than AMSR2 LST because it has continuous spatial texture information and no obvious boundary reconstruction effect. After verifying the accuracy of GF-LST products through simulated gap region validation and in-situ validation, it can be found that: (1) DNN-LST in simulated gap regions showed high accuracy during the daytime and nighttime on July 15, 2012-2020, and the mean values of bias and RMSE compared with AMSR2 LST at day (night) were respectively -0.08K (-0.22K) and 1.89K (2.23K); (2) the accuracy of DNN-LST was the best in autumn (mean RMSE values of 1.43K at day, 1.89K at night) and the worst in winter (mean RMSE values of 2.35K at day, 2.36K at night), no matter during daytime or nighttime, in different seasons in 2015-2017; (3) the RMSE value of DNN-LST during nighttime was slightly higher than the RMSE value of DNN-LST during daytime; (4) the accuracy of DNN-LST was equivalent to AMSR2 LST, that is, the ubRMSE of DNN-LST and AMSR2 LST was all about 4K compared with In-situ LST, but the ubRMSE of DNN-LST was slightly lower than AMSR2 LST. The above accuracy validation analysis shows that DNN-LST has good robustness and good spatial consistency with AMSR2 LST and can be well used to fill the orbital gap of AMSR2 LST to generate spatial seamless GF-LST product.

A constrained boundary gradient reconstruction method for unstructured finite volume discretization of the Euler equations

We propose a novel boundary gradient and solution reconstruction approach for the second-order cell-centered unstructured finite volume method for solving the inviscid Euler equations. The proposed constrained reconstruction method involving ghost cells is shown to be more accurate than several conventional boundary reconstruction methods and linear-exact in the near-boundary areas. In the present procedure, the solutions at the ghost cell centroids are given by solving constraint equations, which are established based on boundary conditions. At the same time, the solution gradients in boundary cells and the solutions in boundary surfaces are obtained altogether, while guaranteeing the compatibility of the boundary conditions with the reconstructed results. A variety of numerical test cases show that the new method effectively reduces the errors of near-boundary approximations and improves the overall numerical accuracy. Furthermore, because the constrained reconstruction is only used for the boundary cells, the extra computational cost barely changes the overall computational efficiency.

The imposition of nonconforming Neumann boundary condition in the material point method without boundary representation

Since its original formulation, the material point method (MPM) has been repeatedly further developed to become a powerful tool for simulating large deformation problems. However, the imposition of boundary condition in the MPM remains a challenge since most material points are not located at the boundary and regular background mesh is most commonly used. Therefore, the existing methods to impose boundary condition always require a boundary tracking or reconstruction algorithm, which is not always efficient or accurate. In the current work, a novel strategy to apply nonconforming Neumann boundary condition is proposed that does not require the exact boundary position. The original problem with a nonconforming traction boundary condition is transformed into an equivalent problem with a prescribed virtual stress field. Importantly, both the original and the transformed problems produce the exact same response within the material domain. To solve the equivalent problem, a modified governing equation without boundary representation is subsequently constructed, where the volume integral terms are computed by both particle quadrature and cell quadrature. Several numerical examples are investigated to assess the accuracy and demonstrate the capability of the proposed approach in simulating different engineering problems. These numerical examples include mesh refinement to illustrate the method’s good convergence and a 3D complex surface to illustrate the method’s capability.

Accuracy of intraoperative bone registration and stereotactic boundary reconstruction during total knee arthroplasty surgery.

The intraoperative registration of the bones play a crucial role in image-based computer-assisted knee arthroplasty to achieve accurate implant placement and to create reliable stereotactic bone boundaries for robot-assisted surgical systems. This study assessed the intraoperative registration accuracy on six intact fresh frozen cadavers. Rotational errors around the mechanical axis were the largest, with a standard deviation of 1.2° and outliers up to 3.7°. The mean translational errors were lower than 1mm, with outliers up to 1.5mm. These errors were amplified to 2mm for the registration-based reconstruction of the posterior bone surface at the resection levels. Given the cumulative behaviour of surgical errors, registration errors can affect the final implant positioning. Furthermore, inaccuracies in the reconstructed bone boundary directly affect the virtual stereotactic boundaries used in robotic-assisted surgery and can result in an incomplete resection or inadvertent soft tissue damage.

Cartographic reconstruction of administrative boundaries for the Catholic Church

Cartographic reconstruction of administrative boundaries for the Catholic Church

An Extremely Effective Spatial Pyramid and Pixel Shuffle Upsampling Decoder for Multiscale Monocular Depth Estimation.

To estimate the accurate depth from a single image, we proposed a novel and effective depth estimation architecture to solve the problem of missing and blurred contours of small objects in the depth map. The architecture consists of Extremely Effective Spatial Pyramid modules (EESP) and Pixel Shuffle upsampling Decoders (PSD). The results of this study show that multilevel information and the upsampling method in the decoders are essential for recovering the accurate depth map. Through the model we proposed, competitive performance compared with state-of-the-art methods in terms of reconstruction of object boundaries and the detection rate of small objects has been demonstrated. Our approach has wide applications in higher-level visual tasks, including 3D reconstruction and autonomous driving.

Grain boundary modification of multi-main-phase Nd0.7(La, Ce)0.3-Fe-B magnet towards 2 T coercivity

Effective grain boundary (GB) reconstruction process has been proposed by introducing Pr-Fe-Al-Ga intergranular additive in the B-lean Nd-La-Ce-Fe-B multi main phase (MMP) magnets. A coercivity of ~2.0 T was yielded in the Nd-Fe-B sintered magnet with 24 wt% Nd substituted by La-Ce. Detailed structural analysis revealed that the RE6Fe13(Ga, Al)1 phase was apparently formed in the triple junction area, triggered by the conducive intergranular composition environment provided by the B-lean composition and the Pr-Fe-Al-Ga addition. Simultaneously, continuous nonferromagnetic GB phases were generated to decouple the intergranular exchange, accompanied by the suppressed fraction of REFe2 and REOx phases. Elemental distribution analysis demonstrated that Pr preferred to enter La/Ce-rich grains to form a Pr-rich shell that enhanced the magnetocrystalline anisotropy field of La/Ce-rich grain surface. Overall, the Pr-rich magnetic hardening shells and the reconstruction GB structure jointly gave rise to the restrained reversion of magnetic domains, thus an extraordinary coercivity was achieved in the Nd-La-Ce-Fe-B magnet. These phenomena may provide a new insight for the development of high-figure-of-merit Nd-La-Ce-Fe-B permanent magnets.

Switching Crystallographic Chirality in Ba(TiO)Cu4(PO4)4 by Laser Irradiation.

Switching crystallographic chirality is nontrivial because there is no simple conjugate field to chirality. Here we demonstrate chirality switching in an inorganic crystalline material by manipulating the boundaries of chiral domains with laser irradiation. Our study material is Ba(TiO)Cu4(PO4)4, exhibiting a chiral structure at room temperature and a chiral-achiral phase transition at 710 °C. By irradiation of a laser beam with a wavelength at which Ba(TiO)Cu4(PO4)4 exhibits strong optical absorption, local heating is induced. This leads to reconstructions of chiral domain boundaries, revealed by optical rotation measurements. In the reconstruction process, energetically unstable domain boundaries tend to be minimized, affecting resultant domain patterns. On the basis of this feature, we successfully manipulate chiral domain patterns by scanning the laser beam on the sample surface. Our findings provide a unique approach to controlling chirality in inorganic crystalline materials.

Tumor deformation correction for an image guidance system in breast conserving surgery.

Breast cancer is the most common cancer in women, and surgical resection is standard of care for the majority of breast cancer patients. Unfortunately, current reoperation rates are 10-29%. Uncertainty in lesion localization is one of the main factors contributing to these high reoperation rates. This work uses the linearized iterative boundary reconstruction approach to model patient breast deformation due to abduction of the ipsilateral arm. A preoperative supine magnetic resonance (MR) image was obtained with the patient's arms down near the torso. A mock intraoperative breast shape was measured from a supine MR image obtained with the patient's arm up near the head. Sparse data was subsampled from the full volumetric image to represent realistic intraoperative data collection: surface fiducial points, the intra-fiducial skin surface, and the chest wall as measured with 7 tracked ultrasound images. The deformed preoperative arm-down data was compared to the ground truth arm-up data. From rigid registration to model correction the tumor centroid distance improves from 7.3 mm to 3.3 mm, average surface fiducial error across 9 synthetic fiducials and the nipple improves from 7.4 ± 2.2 to 1.3 ± 0.7, and average subsurface error across 14 corresponding features improves from 6.2 ± 1.4 mm to 3.5 ± 1.1 mm. Using preoperative supine MR imaging and sparse data in the deformed position, this modeling framework can correct for breast shape changes between imaging and surgery to more accurately predict intraoperative position of the tumor as well as 10 surface fiducials and 14 subsurface features.

Grain boundary stiffness based on phase field crystal simulations

Phase field crystal modeling with wavelet filtering is shown to be an attractive replacement for molecular dynamics simulations when evaluating grain boundary stiffness by the capillary fluctuation method. Obstacles such as iterative equilibration of grain boundary structures and repeated reconstruction of the grain boundary over extended simulations can be avoided.

Автоматизированное распознавание генетических типов рельефа Кольского полуострова по морфометрическим данным

The automatic geomorphological mapping based on the Earth’s surface remote sensing data has been developed in recent years. The aim of the research is an attempt of automatic creation of the Kola Peninsula geomorphological map at the morphogenetic legend’s principle. It was gained based on the random forest classification technique. As input data a several geomorphometric variables were used only (the basic ones – elevation, slope angle, curvatures etc., and many those of surface texture). Developing such algorithms for different territories and hierarchical levels of landforms analysis contributes to propagate the techniques of the fast geomorphological mapping. On the training data covering only 1,3 % of the study area with known labels for one of thirteen probable landform types, the reconstruction of geomorphological boundaries and the automatic creation of the geomorphological map were carried out. The accuracy of the resulting map was 81 %. Elevation has the greatest discrimination power according to Kola Peninsula landform types. In addition, some area-based local geomorphometric variables characterizing terrain pattern has big discrimination power. The lowest power relates with the “classical” local-based geomorphometric variables. The results of the work can be used in the development of automated landforms mapping systems at the level of morphogenetic types.

Validation of the strike point position estimation with the local expansion method for MAST upgrade on the DIII-D tokamak

A local expansion method has been proposed for estimating the strike point position for the advanced divertor configuration on the MAST Upgrade tokamak. The paper discusses the application and assesses the performance of the technique on a long-legged divertor plasma configuration on an operating device - the DIII-D tokamak. A comparison of the spatial location of the outer strike point estimated with the local expansion method against the plasma boundary reconstruction and divertor diagnostics on the DIII-D tokamak is reported. A good agreement with the equilibrium reconstruction and diagnostic data is achieved with respect to estimation of the spatial location of the outer strike point for the long-legged divertor plasma discharge.

A Deep Learning Image Data Augmentation Method for Single Tumor Segmentation.

PurposeMedical imaging examination is the primary method of diagnosis, treatment, and prevention of cancer. However, the amount of medical image data is often not enough to meet deep learning needs. This article aims to expand the small data set in tumor segmentation based on the deep learning method.MethodsThis method includes three main parts: image cutting and mirroring augmentation, segmentation of augmented images, and boundary reconstruction. Firstly, the image is divided into four parts horizontally & vertically, and diagonally along the tumor’s approximate center. Then each part is mirrored to get a new image and hence a four times data set. Next, the deep learning network trains the augmented data and gets the corresponding segmentation model. Finally, the segmentation boundary of the original tumor is obtained by boundary compensation and reconstruction.ResultsCombined with Mask-RCNN and U-Net, this study carried out experiments on a public breast ultrasound data set. The results show that the dice similarity coefficient (DSC) value obtained by horizontal and vertical cutting and mirroring augmentation and boundary reconstruction improved by 9.66% and 12.43% compared with no data augmentation. Moreover, the DSC obtained by diagonal cutting and mirroring augmentation and boundary reconstruction method improved by 9.46% and 13.74% compared with no data augmentation. Compared with data augmentation methods (cropping, rotating, and mirroring), this method’s DSC improved by 4.92% and 12.23% on Mask-RCNN and U-Net.ConclusionCompared with the traditional methods, the proposed data augmentation method has better performance in single tumor segmentation.

Reconstruction of rainfall region boundaries for the western region found by Dale (1959) in Peninsular Malaysia

Reconstruction of rainfall region boundaries for the western region found by Dale (1959) in Peninsular Malaysia