Search Results (10)

Geometric image transformations are fundamental to image processing, computer vision and graphics, with critical applications to pattern recognition and facial identification. The splitting-integrating method (SIM) is well suited to the inverse transformation $T^{-1}$ of digital images and patterns, but it encounters difficulties in nonlinear solutions for the forward transformation T. We propose improved techniques that entirely bypass nonlinear solutions for T, simplify numerical algorithms and reduce computational costs. Another significant advantage is the greater flexibility for general and complicated transformations T. In this paper, we apply the improved techniques to the harmonic, Poisson and blending models, which transform the original shapes of images and patterns into arbitrary target shapes. These models are, essentially, the Dirichlet boundary value problems of elliptic equations. In this paper, we choose the simple finite difference method (FDM) to seek their approximate transformations. We focus significantly on analyzing errors of image greyness. Under the improved techniques, we derive the greyness errors of images under T. We obtain the optimal convergence rates $O\left(H^2\right)+O(H/N^2)$ for the piecewise bilinear interpolations ($\mu =1$) and smooth images, where $H(\ll 1)$ denotes the mesh resolution of an optical scanner, and N is the division number of a pixel split into $N^2$ sub-pixels. Beyond smooth images, we address practical challenges posed by discontinuous images. We also derive the error bounds $O\left(H^{\beta }\right)+O(H^{\beta }/N^2)$, $\beta \in (0,1)$ as $\mu =1$. For piecewise continuous images with interior and exterior greyness jumps, we have $O\left(\sqrt{H}\right)+O(\sqrt{H}/N^2)$. Compared with the error analysis in our previous study, where the image greyness is often assumed to be smooth enough, this error analysis is significant for geometric image transformations. Hence, the improved algorithms supported by rigorous error analysis of image greyness may enhance their wide applications in pattern recognition, facial identification and artificial intelligence (AI). Full article

Numerical simulations were conducted to investigate high-pressure water jets in air. The Eulerian multiphase model was employed as the computational framework. Through simulating a high-pressure water jet impinging on a flat plate, two turbulence treatment methodologies were initially examined, demonstrating that the mixture turbulence modeling approach exhibits superior predictive capability compared to the per-phase turbulence modeling approach. Subsequent analysis focused on evaluating turbulence model effects on the impact pressure distribution on the flat plate. The results obtained from the elliptic–blending turbulence model (the SST k-ω-φ-α model) and the other two industry-standard two-equation turbulence models (the realizable k-ε model and the SST k-ω model) were comparatively analyzed against experimental data. The analysis revealed that the SST k-ω-φ-α model demonstrates superior accuracy near the stagnation region. The effects of bubble diameter and surface tension were further examined. Quantitative analysis indicated that the impact pressure exhibits a decrease with decreasing bubble diameter until reaching a critical threshold, below which diameter variations exert negligible influence. Furthermore, surface tension effects were found to be insignificant for impact pressure predictions when the nozzle-to-plate distance was maintained below 100 nozzle diameters (100D). Simulations of free high-pressure water jets were performed to evaluate the model’s capability to predict long-distance jet dynamics. While the axial velocity profile showed satisfactory agreement with experimental measurements within 200D, discrepancies in water volume fraction prediction along the jet axis suggested limitations in phase interface modeling at extended propagation distances. Full article

This study addresses the challenge of efficiently peeling pineapples, which have a distinct elliptical form, thick skin, and small eyes that are difficult to detect with conventional automated methods. This results in significant flesh waste. To improve the process, we developed an integrated system combining an enhanced BlendMask method, termed SAAF-BlendMask, and a Pose Correction Planning (PCP) method. SAAF-BlendMask improves the detection of small pineapple eyes, while PCP ensures accurate posture adjustment for precise path planning. The system uses 3D vision and deep learning technologies, achieving an average precision (AP) of 73.04% and a small object precision (APs) of 62.54% in eye detection, with a path planning success rate reaching 99%. The fully automated electromechanical system was tested on 110 real pineapples, demonstrating a reduction in flesh waste by 11.7% compared to traditional methods. This study highlights the potential of advanced machine vision and robotics in enhancing the efficiency and precision of food processing. Full article

A fully developed turbulent flow in a concentric annulus, Re $=\mathrm{10,000}$, $r_i/r_o=0.5$, with an inner rotating cylinder in the velocity range $N=U_{\omega }/U_b=0÷4$, is studied via a large-eddy simulation. Also, for comparison, simulations by steady-state, unstatiounary RANS k-$\omega$ SST (URANS), and Elliptic Blending Model (EBM) were made. The main focus of this study is on the effect of high rotation on the mean flow, turbulence statistics, and vortex structure. Distribution of the tangential velocity and the Reynolds stress tensor change their behaviour at $N>0.5\sim 1$. With rotation increases, the production of tangential fluctuation becomes dominant over axial ones and the position of turbulent kinetic energy maximum shifts towards the wall into the buffer zone. URANS and EBM approaches show good agreement with LES in mean flow, turbulent statistics, and integral parameters. The difference in pressure loss prediction between LES and URANS does not exceed 20%, but the average difference is about 11%. The EBM approach underestimates pressure losses up to 9% and on average not more than 5%. Vortex structures are described well by URANS. Full article

Using two different methods, a previously developed elliptic blending model (the original $\mathrm{STT} k\text{-}\omega \text{-}\phi \text{-}\alpha$ model) is modified for sensitization to streamline curvature. One method involves modifying the dissipation term in the turbulent dissipation equation, while the other constructs a new formulation for the turbulent kinetic energy production term based on an explicit algebraic stress model. The capabilities of the proposed models are evaluated by applying them to three flows with curved surfaces; namely, the two-dimensional (2D) infinite serpentine passage flow, the 2D U-turn duct flow, and the 2D periodic hill flow. The $\mathrm{STT} k\text{-}\omega$ model with rotation and curvature correction (the $\mathrm{STT} k\text{-}\omega \text{-}CC$ model) is also used for comparison. The computed results are compared with the relevant direct numerical simulation, experimental, and large eddy simulation data from the literature. It is found that the two proposed models significantly improve upon the original $\mathrm{STT} k\text{-}\omega \text{-}\phi \text{-}\alpha$ model. Compared with the $\mathrm{STT} k\text{-}\omega \text{-}CC$ model, the two proposed models produce better results in the 2D infinite serpentine passage flow and the 2D periodic hill flow. The proposed models are similarly competitive with the $\mathrm{STT} k\text{-}\omega \text{-}CC$ model in the 2D U-turn duct flow. Full article

Process-induced changes in the morphology of biodegradable polybutylene adipate terephthalate (PBAT) and polylactic acid (PLA) blends modified with various multifunctional chain-extending cross-linkers (CECLs) are presented. The morphology of unmodified and modified films produced with blown film extrusion is examined in an extrusion direction (ED) and a transverse direction (TD). While FTIR analysis showed only small peak shifts indicating that the CECLs modify the molecular weight of the PBAT/PLA blend, SEM investigations of the fracture surfaces of blown extrusion films revealed their significant effect on the morphology formed during the processing. Due to the combined shear and elongation deformation during blown film extrusion, rather spherical PLA islands were partly transformed into long fibrils, which tended to decay to chains of elliptical islands if cooled slowly. The CECL introduction into the blend changed the thickness of the PLA fibrils, modified the interface adhesion, and altered the deformation behavior of the PBAT matrix from brittle to ductile. The results proved that CECLs react selectively with PBAT, PLA, and their interface. Furthermore, the reactions of CECLs with PBAT/PLA induced by the processing depended on the deformation directions (ED and TD), thus resulting in further non-uniformities of blown extrusion films. Full article

As computational fluid dynamics (CFD) advances, entropy generation minimization based on CFD becomes attractive for optimizing complex heat-transfer systems. This optimization depends on the accuracy of CFD results, such that accurate turbulence models, such as elliptic relaxation or elliptic blending turbulence models, become important. The performance of a previously developed elliptic blending turbulence model (the $\mathrm{SST} k\text{–}\omega \text{–}\phi \text{–}\alpha$ model) to predict the rate of entropy generation in the fully developed turbulent circular tube flow with constant heat flux was studied to provide some guidelines for using this class of turbulence model to calculate entropy generation in complex systems. The flow and temperature fields were simulated by using a CFD package, and then the rate of entropy generation was calculated in post-processing. The analytical correlations and results of two popular turbulence models (the realizable k–ε and the shear stress transport (SST) k–ω models) were used as references to demonstrate the accuracy of the $\mathrm{SST} k\text{–}\omega \text{–}\phi \text{–}\alpha$ model. The findings indicate that the turbulent Prandtl number (Pr_t) influences the entropy generation rate due to heat-transfer irreversibility. Pr_t = 0.85 produces the best results for the $\mathrm{SST} k\text{–}\omega \text{–}\phi \text{–}\alpha$ model. For the realizable k–ε and SST k–ω models, Pr_t = 0.85 and Pr_t = 0.92 produce the best results, respectively. For the realizable k–ε and the SST k–ω models, the two methods used to predict the rate of entropy generation due to friction irreversibility produce the same results. However, for the $\mathrm{SST} k\text{–}\omega \text{–}\phi \text{–}\alpha$ model, the rates of entropy generation due to friction irreversibility predicted by the two methods are different. The difference at a Reynolds number of 100,000 is about 14%. The method that incorporates the effective turbulent viscosity should be used to predict the rate of entropy generation due to friction irreversibility for the $\mathrm{SST} k\text{–}\omega \text{–}\phi \text{–}\alpha$ model. Furthermore, when the temperature in the flow field changes dramatically, the temperature-dependent fluid properties must be considered. Full article

On the basis of a previously developed elliptic blending turbulence model (SST–k–ω–φ–α model), a scale-adaptive simulation (SAS) model is developed by following Menter and Egorov’s SAS concept. An SAS source term, which is related to the ratio of the modeled turbulence scale to the von Kármán length scale, is introduced into the corresponding length-scale determining equation. The major motivation of this study is that the conventional unsteady Reynolds-averaged Navier–Stokes (URANS) models provide only large-scale unsteadiness. The introduction of the SAS term allows the proposed SAS model to dynamically adjust to resolved structures in a URANS framework because this term is sensitive to resolved fluctuations. The predictive capabilities of the proposed SAS model are demonstrated by computing the complex flow configurations in three cases with flow separation from curved surfaces, namely, three-dimensional (3D) diffuser flow, two-dimensional (2D) periodic hills flow, and 2D U-turn duct flow. For comparison, the results predicted by the SST–k–ω–φ–α model and the Menter and Egorov’s SAS model (SST–SAS) are provided. The results are also compared with the relevant experimental, direct numerical simulation, and large eddy simulation data. The results show that the SST–k–ω–φ–α model cannot capture the critical features for all three flows, and that the SST–SAS model is able to predict the results reasonably well. The proposed SAS model is capable of resolving more portions of the turbulence structures, and it yields the best results in all the cases. Full article

Sea surface temperature (SST) is critical for global climate change analysis and research. In this study, we used visible and infrared scanning radiometer (VIRR) sea surface temperature (SST) data from the Fengyun-3C (FY-3C) satellite for SST analysis, and applied the Kalman filtering methods with oriented elliptic correlation scales to construct SST fields. Firstly, the model for the oriented elliptic correlation scale was established for SST analysis. Secondly, observation errors from each type of SST data source were estimated using the optimal matched datasets, and background field errors were calculated using the model of oriented elliptic correlation scale. Finally, the blended SST analysis product was obtained using the Kalman filtering method, then the SST fields using the optimum interpolation (OI) method were chosen for comparison to validate results. The quality analysis for 2016 revealed that the Kalman analysis with a root-mean-square error (RMSE) of 0.3243 °C had better performance than did the OI analysis with a RMSE of 0.3911 °C, which was closer to the OISST product RMSE of 0.2897 °C. The results demonstrated that the Kalman filtering method with dynamic observation error and background error estimation was significantly superior to the OI method in SST analysis for FY-3C SST data. Full article

In this paper, the discrete phase model (DPM) was introduced to study the fuel injector cavitations process and the macro spray characteristic of three different types of nozzle spray shape with diesel and hybrid biofuel blend for several injection pressures and backpressures. The three types of nozzle spray shapes used were circle, elliptical A type, and elliptical B type. The cavitations’ flows inside the injector nozzles were simulated with Computer Fluid Dynamics (CFD) simulations using the cavitations mixture approach. The effect of nozzle spray shape towards the spray characteristic of hybrid biofuel blends is analyzed and compared with the standard diesel. Furthermore, a verification and validation from both the experimental results and numerical results are also presented. The nozzle flow simulation results indicated that the fuel type did not affect the cavitation area vastly, but were more dependent on the nozzle spray shape. In addition, the spray width of the elliptical nozzle shape was higher as compared to the circular spray. Moreover, as the backpressure increased, the spray width downstream increased as well. The spray tip penetration for the elliptical nozzle shape was shorter than the circular nozzle shape due to circular nozzles having smaller nozzle widths and lesser spray cone angles. Thus, this resulted in smaller aerodynamic drag. Full article