Smooth Regions Research Articles

Direct joining of quartz glass and copper by nanosecond laser

In present study, quartz glass and copper, which are with a large difference of coefficient of thermal expansion by 38 times, were successfully welded without any interlayer by nanosecond (ns) laser under non-optical contact for the first time. By reasonably tuning the welding parameters, well-formed quartz glass/copper joints without any defects such as microcracks or voids can be achieved. The welded seam includes laser-unirradiated smooth region and laser-irradiated spindle melted region and both the region are composed of “Cu2O″-SiO2 system (Cu–O–Si system) and CuO. The formation of such a particular microstructure feature is attributed to the recoil pressure from ns laser ablation and the Marangoni convection at the interface. The parameters of ns laser welding including laser power, scanning velocity and the number of scans influence the laser energy input and thermal accumulation greatly during welding, thus affecting the interfacial feature and the mechanical property of the resultant joints. The shear strength of the joint can reach 33.4 MPa, which is about 80% of quartz glass shear strength. The metallurgical bonding from interfacial reaction and mechanical interlocking from physical spindle structures are the main reasons for achieving a high shear strength of the joint. We expect this study could provide a new idea for joining materials with large differences in thermophysical properties.

A dependence of binary and planetary system destruction on subtle variations in the substructure in young star-forming regions

ABSTRACT Simulations of the effects of stellar fly-bys on planetary systems in star-forming regions show a strong dependence on subtle variations in the initial spatial and kinematic substructure of the regions. For similar stellar densities, the more substructured star-forming regions disrupt up to a factor of 2 more planetary systems. We extend this work to look at the effects of substructure on stellar binary populations. We present N-body simulations of substructured, and non-substructured (smooth) star-forming regions in which we place different populations of stellar binaries. We find that for binary populations that are dominated by close (<100 au) systems, a higher proportion are destroyed in substructured regions. However, for wider systems (>100 au), a higher proportion are destroyed in smooth regions. The difference is likely due to the hard–soft or fast–slow boundary for binary destruction. Hard (fast/close) binaries are more likely to be destroyed in environments with a small velocity dispersion (kinematically substructured regions), whereas soft (slow/wide) binaries are more likely to be destroyed in environments with higher velocity dispersions (non-kinematically substructured regions). Due to the vast range of stellar binary semimajor axes in star-forming regions (10−2 to 104 au), these differences are small and hence unlikely to be observable. However, planetary systems have a much smaller initial semimajor axis range (likely ∼1–100 au for gas giants) and here the difference in the fraction of companions due to substructure could be observed if the star-forming regions that disrupt planetary systems formed with similar stellar densities.

Combining transformers with CNN for multi-focus image fusion

Recently, deep convolutional neural network (CNN) based methods for multi-focus image fusion have achieved adequate performance. However, most of them cannot obtain spatially continuous results, especially in smooth regions and edges between focused and defocused regions. In this paper, we propose a novel end-to-end method, which merits both Transformers and CNNs, as a strong alternative for multi-focus image fusion task. Transformer has advantages over a CNN in that it can extract global features. It is able to make the fusion results to be spatially consistent. The proposed architecture consists of CNN and transformer branches, where transformer branches take feature map patches as inputs and leverages the transformer to propagate global contexts among patches. Moreover, in order to improve feature representation, we introduce online knowledge distillation learning strategy (KDL). The strategy achieves better interactions between global features and local features. Specifically, we design hard target and soft target by simply yet effectively ensembling outputs of two branches, which are used to supervise CNN and transformer branches. The experiments demonstrate the superiority of our proposed architecture and achieve competitive results with state-of-the-art methods.

Poisson image restoration via an adaptive Euler’s elastica regularization

Many recent studies have shown that Euler’s elastica regularization performs better than the famous total variation (TV) regularization on keeping image features in smooth regions during the process of denoising. In addition, an adaptive weighted matrix combined with total variation is a key technique for well restoring local features of image. Considering these two factors, in this paper, we propose an adaptive Euler’s elastica model for Poisson image restoration so as to well preserve both image features in smooth regions and local features of image. To solve this non-smooth and non-convex model efficiently, we design an alternating direction method of multipliers. Experiments on both natural and synthetic images illustrate the effectiveness and efficiency of the proposed method over the state-of-the-art methods in Poisson restoration and denoising, respectively. In particular, for Poisson restoration, our proposed method improves the TV method up to 2.46 about PSNR for dealing with the Peppers image with Gaussian blur and noise level σ = 1. In addition, the proposed method for Poisson denoising gets higher PSNR and SSIM values than the TAC method, while costing less CPU time.

A kinetic scheme with variable velocities and relative entropy

A new kinetic model is proposed where the equilibrium distribution with bounded support has a range of velocities about two average velocities in 1D. In 2D, the equilibrium distribution function has a range of velocities about four average velocities, one in each quadrant. In the associated finite volume scheme, the average velocities are used to enforce the Rankine–Hugoniot jump conditions for the numerical diffusion at cell-interfaces, thereby capturing steady discontinuities exactly. The variable range of velocities is used to provide additional diffusion in smooth regions. Further, a novel kinetic theory based expression for relative entropy is presented which, along with an additional criterion, is used to identify expansions and smooth flow regions. Appropriate flow tangency and far-field boundary conditions are formulated for the proposed kinetic model. Several benchmark 1D and 2D compressible flow test cases are solved to demonstrate the efficacy of the proposed solver.

An efficient scaling of WENO-JS weights for accuracy preserving and higher resolution schemes

In this short paper, we present efficient scaling of WENO-JS weights which results in robust and formal accuracy preserving high resolution WENO-JS schemes. The proposed scaling makes the WENO-JS schemes robust in the sense that schemes works well irrespective of the choice for the parameter ϵ used in classical WENO-JS weights to prevent division by zero. In smooth solution region the proposed scaling keeps the scaled WENO weights in the vicinity of critical weights thus resulting scheme retains formal accuracy. Numerical experiments show that the WENO schemes with scaled weights provide higher resolution for discontinuities as well for smooth solution with high gradients.

VLSI implementation of image compressor using probabilistic run length coding

AbstractMultimedia applications, such as image processing including image and video transfer, heavily rely on reduction. The traditional device methods to picture reduction use more space, energy, and processing time. The majority of current efforts use the Golomb‐Rice encoding, due to its larger memory requirement and higher computing difficulty. So, this research concentrated on hardware design‐oriented probability run length (PRL) coding technique based on lossless colour image compression. The block truncation coding (BTC) features of the compression process are used by the suggested PRL method. The proposed image compression hardware consists of various modules such as a Parameter calculator, fuzzy table, bitmap generator, BTC parameters training, prediction, and error control, and PRL‐based finite state machine (PRL‐FSM). The proposed image compressor utilizes the parameter calculator block, which estimates the block type based on the image pixel intensities for each sub‐block. Thus, each block of the image is compressed by using a new block type and generates a variable block size. The proposed method utilizes the PRL‐BTC encoding method, which also calculates the probability of error between the compressed image to the test image. The process is iterated until the performance trade‐off between hardware cost and compression ratio (CR) is achieved. Hence, both smooth regions and non‐smooth regions of images are perfectly compressed by the probability‐based block selection. The simulation results show that the proposed method resulted in a better area, power, delay metrics, peak signal‐to‐noise ratio (PSNR), and CR compared to the state of art approaches.

Emulsification properties of sugar beet pectin: The synergistic effect of homogalacturonan and rhamnogalacturonan-Ⅰ

In recent years, sugar beet pectin has been shown to exhibit excellent emulsifying properties compared to commercial citrus peel pectin and apple pectin, with emulsifying properties similar to those of gum arabic. However, due to the highly complex molecular structure, the emulsification mechanism of sugar beet pectin is still unclear. In this study, the RG-Ⅰ region of sugar beet pectin was successfully isolated and characterized by chemical composition, FT-IR, TG/DTG, XRD and 1H NMR analyses. In addition, multiscale characterization techniques showed that RG-Ⅰ could form a much thicker and more elastic interfacial film than HG. This highly elastic interfacial film is crucial for the long-term emulsion stability. Moreover, our studies also showed that HG and RG-Ⅰ alone could not form an interfacial film as elastic as that of sugar beet pectin. This indicates that the smooth HG region and hairy RG-Ⅰ region of sugar beet pectin molecules are both necessary to form a thick and highly elastic interfacial film, and thus obtain a long-term stable emulsion.

Smoothing the Rough Edges: Evaluating Automatically Generated Multi-Lattice Transitions.

Additive manufacturing is advantageous for producing lightweight components while addressing complex design requirements. This capability has been bolstered by the introduction of unit lattice cells and the gradation of those cells. In cases where loading varies throughout a part, it may be beneficial to use multiple, distinct lattice cell types, resulting in multi-lattice structures. In such structures, abrupt transitions between unit cell topologies may cause stress concentrations, making the boundary between unit cell types a primary failure point. Thus, these regions require careful design to ensure the overall functionality of the part. Although computational design approaches have been proposed, smooth transition regions are still difficult to achieve, especially between lattices of drastically different topologies. This work demonstrates and assesses a method for using variational autoencoders to automate the creation of transitional lattice cells, examining the factors that contribute to smooth transitions. Through computational experimentation, it was found that the smoothness of transition regions was strongly predicted by how closely the endpoints were in the latent space, whereas the number of transition intervals was not a sole predictor.

Fatigue Behaviour of High-Velocity Oxy-Fuel (HVOF) Coated Steel by Finite Element Analysis

High-velocity oxy-fuel (HVOF) spraying is extensively used in a range of industries. This is because it can reduce component wear, erosion, and corrosion. If mechanical qualities and fatigue behaviour are considered, the impact of the HVOF thermal sprayingcoating on the components can be contested. The major goals of this work are to investigate the fatigue properties of carbon steel coated with tungsten carbide-nickel and to use finite element analysis to investigate the fracture process of carbon steel coated with tungsten carbide-nickel. The fatigue test for these studies was conducted in ANSYS Workbench software, where the mean theory is set as Goodman theory. Specimens are modelled in SolidWorks software in a dog-bone shape. The fatigue test simulations are run with the 9 kN, 10.5 kN, 12 kN and 13.5 kN forces applied to one of the specimens' ends and fixed support applied to the other. Based on the result, the coated specimens can sustain longer compared to uncoated specimens, and the higher forces willreduce the lifespan of the specimen. The results also show that uncoated specimens receive more damage at maximum compared to coated specimens, and the higher forces will make the damage received by the specimen higher. For fatigue strength, the uncoated specimens have higher stress compared to coated specimens, and the higher forces will make the fatigue strength of the specimen higher. The result for the fracture shows that uncoated steel has the largest smooth region compared to coated steel.

Image Copy-Move Forgery Detection Based on Fused Features and Density Clustering

Image copy-move forgery is a common simple tampering technique. To address issues such as high time complexity in most copy-move forgery detection algorithms and difficulty detecting forgeries in smooth regions, this paper proposes an image copy-move forgery detection algorithm based on fused features and density clustering. Firstly, the algorithm combines two detection methods, speeded up robust features (SURF) and accelerated KAZE (A-KAZE), to extract descriptive features by setting a low contrast threshold. Then, the density-based spatial clustering of applications with noise (DBSCAN) algorithm removes mismatched pairs and reduces false positives. To improve the accuracy of forgery localization, the algorithm uses the original image and the image transformed by the affine matrix to compare similarities in the same position in order to locate the forged region. The proposed method was tested on two datasets (Ardizzone and CoMoFoD). The experimental results show that the method effectively improved the accuracy of forgery detection in smooth regions, reduced computational complexity, and exhibited strong robustness against post-processing operations such as rotation, scaling, and noise addition.

High-fidelity simulation of blade vortex interaction of helicopter rotor based upon TENO scheme

Numerical simulation methods for unsteady vortex field of helicopter rotor with high resolution and low dissipation TENO8-AA primitive variables reconstruction schemes are established based on moving-embedded grid and Navier-Stokes equations. Firstly, the Targeted Essentially Non-Oscillatory (TENO) scheme are developed by employing ENO-like candidate stencil selection strategy, and the candidate stencil is adopted with optimal weight in smooth region while it is discarded completely in discontinuous region, which reduces the dissipation and dispersion errors and approaches better spectral properties. Then, the aerodynamic characteristics of Helishape-7A model rotor in Blade Vortex Interaction (BVI) state and the flowfield of Lynx rotor in hover are simulated, which validates that the blade tip vortex trajectory with larger wake age and more details of vortex can be captured by TENO8-AA scheme with only a quarter of grid points and half time comparing to WENO-JS scheme. Moreover, the simulation accuracy of thrust coefficient is improved by up to 36%. Finally, the analyses for BVI and aeroacoustic characteristics of Operational Loads Survey (OLS) rotor are conducted, and the different forms of interaction mechanism are explored, such as oblique and parallel interactions. The results indicate that TENO scheme not only ensures the resolution of simulation in discontinuous region, but also minimizes the numerical dissipation in smooth region dominated by blade tip vortex. Therefore, the acoustic pressure peak prediction error of rotor in BVI state is significantly reduced to 5.6% and 0.8% at two microphone locations, respectively.

Application of continuum damage mechanics in fatigue assessment of A516 steel specimens considering residual stresses

The present study evaluates the effects of tensile residual stresses on fatigue behaviour of ASTM A516 pressure vessel steel specimens. In this regard, fatigue specimens containing a smooth notch region are studied. A damage coupled elastic-plastic constitutive material model is developed to investigate effects of residual stresses on fatigue life. Isotropic and kinematic hardening parameters of the material are experimentally determined. Additionally, the damage model parameters are specified from fatigue experiments conducted on standard specimens in different stress ratios. Tensile residual stresses are introduced into the smooth notched specimens through employing four-point-bending method. The hole drilling technique is utilized to measure the residual stress magnitudes. The results indicate that about two third of fatigue life of the specimens is decreased due to the existed tensile residual stresses. Furthermore, fatigue crack initiation and propagation behaviour in the specimens containing residual stress are studied based on the developed continuum damage model.

A Wheeler–DeWitt Quantum Approach to the Branch-Cut Gravitation with Ordering Parameters

In this contribution to the Festschrift for Prof. Remo Ruffini, we investigate a formulation of quantum gravity using the Hořava–Lifshitz theory of gravity, which is General Relativity augmented by counter-terms to render the theory regularized. We are then led to the Wheeler–DeWitt (WDW) equation combined with the classical concepts of the branch-cut gravitation, which contemplates as a new scenario for the origin of the Universe, a smooth transition region between the contraction and expansion phases. Through the introduction of an energy-dependent effective potential, which describes the space-time curvature associated with the embedding geometry and its coupling with the cosmological constant and matter fields, solutions of the WDW equation for the wave function of the Universe are obtained. The Lagrangian density is quantized through the standard procedure of raising the Hamiltonian, the helix-like complex scale factor of branched gravitation as well as the corresponding conjugate momentum to the category of quantum operators. Ambiguities in the ordering of the quantum operators are overcome with the introduction of a set of ordering factors α, whose values are restricted, to make contact with similar approaches, to the integers α=[0,1,2], allowing this way a broader class of solutions for the wave function of the Universe. In addition to a branched universe filled with underlying background vacuum energy, primordial matter and radiation, in order to connect with standard model calculations, we additionally supplement this formulation with baryon matter, dark matter and quintessence contributions. Finally, the boundary conditions for the wave function of the Universe are imposed by assuming the Bekenstein criterion. Our results indicate the consistency of a topological quantum leap, or alternatively a quantum tunneling, for the transition region of the early Universe in contrast to the classic branched cosmology view of a smooth transition.

A new smoothed particle hydrodynamics method based on high-order moving-least-square targeted essentially non-oscillatory scheme for compressible flows

In this study, we establish a hybrid high-order smoothed particle hydrodynamics (SPH) framework (MLS-TENO-SPH) for compressible flows with discontinuities, which is able to achieve genuine high-order convergence in smooth regions and also capture discontinuities well in non-smooth regions. The framework can be either fully Lagrangian, Eulerian or realizing arbitary-Lagrangian-Eulerian (ALE) feature enforcing the isotropic particle distribution in specific cases. In the proposed framework, the computational domain is divided into smooth regions and non-smooth regions, and these two regions are determined by a strong scale separation strategy in the targeted essentially non-oscillatory (TENO) scheme. In smooth regions, the moving-least-square (MLS) approximation is used for evaluating high-order derivative operator, which is able to realize genuine high-order construction; in non-smooth regions, the new TENO scheme based on Vila's framework with several new improvements will be deployed to capture discontinuities and high-wavenumber flow scales with low numerical dissipation. The present MLS-TENO-SPH method is validated with a set of challenging cases based on the Eulerian, Lagrangian or ALE framework. Numerical results demonstrate that the MLS-TENO-SPH method features lower numerical dissipation and higher efficiency than the conventional method, and can restore genuine high-order accuracy in smooth regions. Overall, the proposed framework serves as a new exploration in high-order SPH methods, which are potential for compressible flow simulations with shockwaves.

DDL-MVS: Depth Discontinuity Learning for Multi-View Stereo Networks

We propose an enhancement module called depth discontinuity learning (DDL) for learning-based multi-view stereo (MVS) methods. Traditional methods are known for their accuracy but struggle with completeness. While recent learning-based methods have improved completeness at the cost of accuracy, our DDL approach aims to improve accuracy while retaining completeness in the reconstruction process. To achieve this, we introduce the joint estimation of depth and boundary maps, where the boundary maps are explicitly utilized for further refinement of the depth maps. We validate our idea by integrating it into an existing learning-based MVS pipeline where the reconstruction depends on high-quality depth map estimation. Extensive experiments on various datasets, namely DTU, ETH3D, “Tanks and Temples”, and BlendedMVS, show that our method improves reconstruction quality compared to our baseline, Patchmatchnet. Our ablation study demonstrates that incorporating the proposed DDL significantly reduces the depth map error, for instance, by more than 30% on the DTU dataset, and leads to improved depth map quality in both smooth and boundary regions. Additionally, our qualitative analysis has shown that the reconstructed point cloud exhibits enhanced quality without any significant compromise on completeness. Finally, the experiments reveal that our proposed model and strategies exhibit strong generalization capabilities across the various datasets.

A sixth-order central WENO scheme for nonlinear degenerate parabolic equations

In this paper, we develop a new sixth-order finite difference central weighted essentially non-oscillatory (WENO) scheme with Z-type nonlinear weights for nonlinear degenerate parabolic equations. The centered polynomial is introduced for the WENO reconstruction to avoid the negative linear weights. We choose the Z-type nonlinear weights based on the $$L^2$$ -norm smoothness indicators, yielding the new WENO scheme with less computational cost. It is also confirmed that the proposed central WENO scheme with the devised nonlinear weights achieves sixth order accuracy in smooth regions. One- and two-dimensional numerical examples are presented to demonstrate the improved performance of the proposed central WENO scheme.

Novel TENO schemes with improved accuracy order based on perturbed polynomial reconstruction

Firstly, an improved TENO scheme based on perturbed polynomial reconstruction (TENO-P) is proposed for hyperbolic conservation laws on the foundation of fifth-order TENO5 scheme. Two different free-parameters are introduced into the reconstruction coefficients to eliminate the third-order errors in the candidate stencils and the fifth-order error in the global stencil, respectively. One-order of accuracy improvement is achieved by adaptively adjusting the values of the free-parameters, resulting a maximum sixth-order accuracy in the smooth stencil. Secondly, to improve the accuracy order of the fifth-order TENO5-THINC scheme, a sixth-order TENO-THINC-P scheme is proposed by combining the proposed TENO-P scheme for smooth regions with the THINC reconstruction for non-smooth discontinuities. Compared to the TENO5 scheme and the TENO5-THINC scheme, the numerical results show the dissipations of the TENO-P scheme and the TENO-THINC-P scheme are reduced, and their resolutions are significantly improved in resolving complicated flow structures with multiple discontinuities. Taking the computational efficiency and the numerical resolution into consideration, the TENO-P scheme is suitable for resolving vortex structures of turbulence while the TENO-THINC-P scheme is more suitable for resolving vortex structures near strong discontinuities. The derivation processes of the TENO-P scheme and the TENO-THINC-P scheme also demonstrate that the perturbed polynomial reconstruction has simple principle and good portability and expandability, so the idea of the TENO-P scheme and the TENO-THINC-P scheme can be easily extended to other improved very-high-order TENO schemes or WENO schemes.

Temporal novelty detection and multiple timescale integration drive Drosophila orientation dynamics in temporally diverse olfactory environments.

To survive, insects must effectively navigate odor plumes to their source. In natural plumes, turbulent winds break up smooth odor regions into disconnected patches, so navigators encounter brief bursts of odor interrupted by bouts of clean air. The timing of these encounters plays a critical role in navigation, determining the direction, rate, and magnitude of insects' orientation and speed dynamics. Disambiguating the specific role of odor timing from other cues, such as spatial structure, is challenging due to natural correlations between plumes' temporal and spatial features. Here, we use optogenetics to isolate temporal features of odor signals, examining how the frequency and duration of odor encounters shape the navigational decisions of freely-walking Drosophila. We find that fly angular velocity depends on signal frequency and intermittency-the fraction of time signal can be detected-but not directly on durations. Rather than switching strategies when signal statistics change, flies smoothly transition between signal regimes, by combining an odor offset response with a frequency-dependent novelty-like response. In the latter, flies are more likely to turn in response to each odor hit only when the hits are sparse. Finally, the upwind bias of individual turns relies on a filtering scheme with two distinct timescales, allowing rapid and sustained responses in a variety of signal statistics. A quantitative model incorporating these ingredients recapitulates fly orientation dynamics across a wide range of environments and shows that temporal novelty detection, when combined with odor motion detection, enhances odor plume navigation.

In situ observation of glass-like fragmentation of high-temperature silicate melts generating fine ashes

Volcanic ash originating from the fragmentation of magma damages infrastructure and the environment. Bubble expansion is crucial in magma fragmentation, but low-intensity eruptions frequently emit ashes with fewer bubbles. We here conducted tensional experiments on silicate melt at a high temperature, at which the melt elongates or fractures depending on the strain rate. A fracture occurs by appearing of a crack on the melted silicate rod, followed by a generation of small fragments. The fracture surface shows a smooth and rough region dichotomy, similar to those observed on glass fracture surfaces at room temperature. The rough surface region generates small fragments. Interestingly, the measured stress-strain curves indicate fragmentation occurs under viscous deformation. These results suggest that silicate melts under viscous deformation fragment, as glass does at room temperature. The ductility around the crack tip promotes void nucleation and coalescence, causing the crack to branch to generate dense, fine volcanic ashes.