Nonlinear Interpolation Method Research Articles

Numerical simulation and experimental research of fiber motion in vortex spinning

The application of high speed air flow in the textile field represents the frontier development direction in this field. However, the coupling mechanism between air flow and fiber is extremely complicated which greatly limits the development and application of new textile technologies. For this reason, this research study is intended to focus on the common cutting-edge basic scientific problem of the air-flow-fiber coupling mechanism, the vortex spinning technology is taken as a breakthrough point for research. Three-dimensional numerical models of air flow in vortex spinning nozzle and a free-end fiber were established. The hybrid grids including the structured hexahedral grids and the unstructured tetrahedral grids were used to divide the air-flow computational region, the realizable κ- ε model was used to solve the turbulent characteristics of air flow, and the wall function method was used to solve the air flow in the near wall region. The displacement and deformation of a single free-end fiber under the action of the air-flow force was solved by the second-order nonlinear double asymptotic method and interpolation method. The dynamic twist process of a free-end fiber was simulated in three-dimensional space by taking into account the fiber characteristics, such as straightening, bending, and torsion. In addition, a high magnification microscope was used to observe the free-end fiber motion during the spinning process. The results show that the numerical simulation is consistent with the experimental observation, proving that dynamic numerical simulation can solve difficult problems in the unobserved dynamic twisting process, and this deepens the understanding of the spinning mechanism in vortex spinning.

Image Interpolation with Regional Gradient Estimation

This paper proposes an image interpolation method with regional gradient estimation (GEI) to solve the problem of the nonlinear interpolation method not sufficiently considering non-edge pixels. First, the approach presented in this paper expanded on the edge diffusion idea used in CGI and proposed a regional gradient estimation strategy to improve the problem of gradient calculation in the CGI method. Next, the gradient value was used to determine whether a pixel was an edge pixel. Then, a 1D directional filter was employed to process edge pixels while interpolating non-edge pixels using a 2D directionless filter. Finally, we experimented with various representative interpolation methods for grayscale and color images, including the one presented in this paper, and compared them in terms of subjective results, objective criteria, and computational complexity. The experimental results showed that GEI performed better than the other methods in an experiment concerning the visual effect, objective criteria, and computational complexity.

Statistical data expansion using Kriging for probabilistic capacity factor calibration

This study proposes a new reliability-based capacity factor calibration method based on the EN 1990 Annex D method in combination with Kriging for a statistical data expansion. The original EN 1990 Annex D method has been widely used in partial safety factor or capacity factor calibrations in international structural design standards by rigorously considering the modelling error of the design equations in comparison with real experimental data. However, as the number of experimental data is often limited in practical situations, large statistical uncertainty needs to be incorporated in the safety factor calibration process, and the calibrated partial safety factors or capacity factors have large variations. In the proposed method, Kriging, a data-driven nonlinear interpolation method, is utilised to statistically expand the experimental database used for modelling error estimation when experimental data are limited. To make the calculation rigorous, the Kriging error of the statistically expanded data is also estimated and incorporated into the proposed framework. The proposed method is demonstrated through two numerical examples and three real world structural design examples including the shear strength of reinforced concrete beams and the axial resistance of concrete-filled steel tubular stub columns with circular and rectangular sections, each of which has more than 300 experimental data for verification. The results show that the proposed method always improves the calibration results by statistical data expansion, which does not need any additional physical costs for experiments.

Comparison of boundary interpolation methods on the geometrical modeling of viscosity for CaO-Al2O3-SiO2 melts

Double Line (DL) model is an efficient method for predicting the physicochemical properties of systems with limited solubility area, and linear interpolation is always taken for the boundary-property interpolation. In this paper, two nonlinear interpolation methods are introduced to optimize the interpolated results on the calculation boundary, which are used for the viscosity prediction of CaO-Al2O3-SiO2 system by DL model. The predicted results by two nonlinear interpolation methods show better agreements with the experimental data than those by linear interpolation. Besides, whatever the interpolation method is, the predicted mean deviations by DL model are always much smaller than those by empirical models (Ray model and Urbain model). It is anticipated that the introduction of nonlinear interpolation methods will improve the calculation accuracy of ternary melts by DL model.

VERIFICATION AND VALIDATION OF BACK-END CYCLE SOURCE TERM CALCULATION OF THE NODAL CODE RAST-K

Verification and validation (V&V) results of source term calculation capability implemented in the nodal diffusion code RAST-K are presented in this paper. An isotope inventory prediction method is presented in this work which is implemented with RAST-K and the lattice code STREAM. STREAM generates cross-section and provides number density information by history branch calculations. RAST-K supplies the power history and three history indexes (boron concentration, moderator temperature and fuel temperature). The main feature of the newly implemented spent nuclear fuel (SNF) characterization is the direct consideration of three-dimensional (3D) core simulation conditions by using operation history information. As a result of this, it could reduce the computation time. The implemented SNF analysis capability have two main functions. The first is to predict isotope inventory by Lagrange non-linear interpolation method, using power history correction factors. The second is to calculate the radiological response activity, decay heat, and neutron/gamma source strengths. The V&V of these two functions are thus presented herein. The isotope inventory prediction is validated with measured data from ten SNF samples of Takahama-3 and six samples of Calvert Cliffs-1 pressurized water reactors (PWR). Eighteen decay heat measurements of Ringhals Unit 3 PWR fuel assemblies are then employed to validate the decay heat calculation results. In addition, STREAM is employed in a code-to-code comparison for verification. The fuel assemblies cover the burnup range 14.3 - 47.25 GWd/tU, initial enrichment of 2.1 - 4.11 235U w/o and cooling time of 3.96 to 20.01 years. The comparison to STREAM shows the accuracy of the RAST-K SNF and prediction of the decay heat is within 4%. Overall, this paper demonstrates that RAST-K SNF calculation can be applied to the back-end cycle source term analysis.

Flexible Data Rate V2X Communication System beyond 1.84 Gb/s Based on MIMO VLC and Radar Integration

Vehicle-to-everything (V2X) communication has been widely studied in recent years for the rapid development of the vehicular traffic. In this paper, a V2X communication system integrating the probabilistic shaping (PS) bitloading multi-input-multi-output (MIMO) visible light communication (VLC) and the millimeter wave radar is proposed. The PS bitloading algorithm utilizes the full spectrum resource of the LED headlights, and the MIMO configuration enhances the performance of the VLC system. Furthermore, the linear and nonlinear interpolation method makes it possible to calculate the SNR at every point from the SNR measured at several discrete calibration points. The SNR table enables the radar to guide the VLC according to the distance, achieving the highest achievable information rate (AIR) at every point. The system supports the V2X communication beyond 1.1 Gb/s up to 5 m. This is the first VLC based V2X sensing and communication system, and the AIR in the system is 1.8484 Gb/s. As far as we know, it is the highest data rate reported in the LED headlight based VLC system.

A morphing-Based 3D point cloud reconstruction framework for medical image processing

Background and Objective: In the virtual surgery simulation system, the reconstruction of a highly precise soft tissue 3D model is an effective method to improve the user’s visual telepresence. However, the traditional point cloud generation method based on subdivision and filling is unsatisfactory due to its low accuracy and slow speed.Methods: To address this problem, we present a novel 3D point cloud reconstructing model based on Morphing. The 3D surface model of soft tissue (live) is obtained from a series of 2D CT images using Mimics. The 3D voxel model of soft tissue is reconstructed through a sequential change of the 3D surface model by utilizing Morphing. A nonlinear interpolation method is used to fit the irregular shape of the model and improve simulation accuracy.Results: The point cloud model builds from discrete points, avoiding the problems of instability and computational complexity, which are inherent in both the surface and volume models for soft tissue. Compared with the volumetric subdividing and voxel filling method, the simulation results show that the 3D cloud model reconstructed based on Morphing is more fast, accurate and consistent with the real soft tissue.Conclusions: The simulating experiment of soft tissue deformation using 3D point cloud model which reconstructed using moprhing proved our method is effective and correct.

Convolutional neural network driven design optimization of acoustic metamaterial microstructures

The design of broadband mechanical metamaterials in the context of acoustics can be driven by the invariance of the wave equation under a set of special coordinate transformations called transformation acoustics. A program of homogenization to design the metamaterial structure can be derived from these transformation functions subject to geometric constraints from the metamaterial’s intended application. The limits of homogenization in a nonperiodic, nonlinear environment however must be accounted for and corrected. This can be done by means of nonlinear manifold interpolation methods, the feedback into which is driven by the scattered wave field in the ambient medium. The feedback is minimized using statistical and machine learning techniques, dictating the final metamaterial structure. The performance of this algorithmic method is compared against a “brute force” optimization approach driven by a convolutional neural network with no transformation of the underlying wave equation.

Evaporation heat transfer and pressure drop characteristics of R1234ze(E)/R32 as a function of composition ratio in a brazed plate heat exchanger

This study investigates the evaporation heat transfer coefficient and two-phase frictional pressure drop of refrigerant mixture R1234ze(E)/R32 at various R1234ze(E) composition ratios in a brazed plate heat exchanger. The heat transfer coefficient of R1234ze(E)/R32 shows a concave curve as a function of composition ratio owing to the temperature glide of the mixture, whereas the two-phase frictional pressure drop increases exponentially with respect to the composition ratio. In addition, the averaged evaporation heat transfer characteristics of R32, R1234ze(E)/R32 (85%/15%), and R1234ze(E) are compared by considering the European Union (EU) regulations for global warming potential (GWP). For regulation phase A (GWP > 750), R32 exhibits the best heat transfer performance, whereas for regulation phase B (GWP > 150), R1234ze(E) shows a favorable averaged heat transfer coefficient compared to R410A and R134a. Finally, based on the measured data, correlations for the Nusselt number and two-phase friction factor for R1234ze(E)/R32 are derived as a function of composition ratio using a nonlinear interpolation method with the pre-developed correlations for pure R1234ze(E) and R32.

Optimizing design on the wide-band absorbing plasma using fluorescent lamps

The plasma was generated using the fluorescent lamp array and the generating principle was the glow discharge mode. The electron density and angular frequency of the plasma could be adjusted with the electronic ballast by changing the lamp input power. The microwave measurement system was built to get the transmission parameter as a function of the lamp input power and the frequency. The transmission parameter expression as functions of the plasma electron density and the electron collision frequency was deduced, and the optimized function could be established. Then the electron density and the electron collision frequency could be fit using a nonlinear least square interpolation method in the MATLAB software kit. The effective permittivity and permeability of the equivalent plasma absorber could be calculated, the real permittivity decreased and the imaginary permittivity increased as the lamp power increased. As the lamps filled with plasma were aligned with different duty ratio, the reflection and transmission parameter could be simulated in the Computer Simulation Technology (CST) software, and the equivalent permittivity was calculated. Finally, the genetic algorithm was used to optimize the structure of the plasma in two cases (lamps aligned adjacently or dispersed with space) as the reflection loss (RL) was set less than −10 dB in 1–8 GHz. The results showed that as the lamps were distributed adjacently, the lamp powers were of two kinds and the total layer number was 28, the minimum RL was −47.1 dB at 5.1 GHz. While as the lamp power was the same 25 W and the lamp layer alignment was different, the minimum RL was −38.2 dB at 5.7 GHz, the total layer number was only 9 and much smaller than that in the first case.

Simplified temperature-dependent elasto-viscoplastic deformation and fracture modeling of a talcum-filled PP/PE co-polymer

Thermoplastic polymers are widely used in the automotive industry, however, for industrial crash applications there is no generally agreed constitutive theory for modeling large deformations of the rate- and temperature-dependent, non-linear, elasto-viscoplastic material behavior, especially for crash load cases around the glass transition temperature. Nevertheless, for simulating the material response, a prediction model capturing the polymer specific features is required. Therefore, in this work a temperature-dependent material model is presented for a talcum-filled polypropylene/polyethylene co-polymer. The model predicts the rate-dependent deformation and fracture behavior at different ambient temperatures and stress states. It has been implemented in a user material subroutine for an explicit crash code, based on a profound material characterization at −35∘C, 20∘C and 90∘C, covering the load cases uni-axial tension, bi-axial tension, uni-axial compression and shear. For the parameterization and calibration of the model, a parameter identification procedure is presented using a non-linear interpolation method, based on uni-axial tensile tests in between the aforementioned fully characterized ambient temperatures. These additional tests are utilized for obtaining the variation of the most important mechanical properties such as the elastic modulus, the strain hardening, the non-linear plastic Poisson's ratio and the fracture strain over the desired range of ambient temperatures. The model is validated utilizing bi-axial tension tests and glove box flap component punch tests at combinations of ambient temperatures and stress states which have not been used for characterization. The numerical predictions were in good agreement with the experimental observations.

An Efficient Satellite Image Super Resolution Technique for Shift-Variant Images using Improved New Edge Directed Interpolation

Super resolution is a method that reconstructs a higher resolution image from single captured image or set of captured low resolution images. Super resolution imaging is used for several image processing applications like medical imaging, earth observation systems and surveillance systems. Image interpolation is one of the conventional methods used to enhance the resolution of the image. Basic linear interpolation methods like bilinear, bicubic give the blurred image as a result. Non-linear interpolation methods like New Edge Directed Interpolation (NEDI), Curvature based interpolation, neural network based interpolation enhance the image but has limitations like several artifacts. In this paper, a novel innovative approach is proposed in which using dual tree complex wavelet transform (DT-CWT), low and high frequency sub bands are generated. High frequency sub band images are interpolated using improved NEDI which is NEDI with a circular window and dynamic window. Improved NEDI (INEDI) algorithm proposed in the paper gives better results on high frequency components which lead to high resolution image without artifacts. Inverse DT-CWT is applied on interpolated sub bands to reconstruct high resolution image. Registration is applied on both images and shift adaptable bilinear interpolation is applied which reconstructs image into 4 interpolation factor. The proposed approach is verified for different interpolation factors and for different satellite images. The accuracy of proposed approach is verified by several contrast features. The algorithm proposed in this paper outperforms in comparison to state of the art algorithms.

Application of RFID Technology in Urban Underground Comprehensive Pipe Gallery

This paper designs a kind of comprehensive pipe gallery patrol and positioning system based on RFID, in order to solve the problems of low work quality, poor reliability, easy loss of information and difficult to keep, etc. Firstly, many groups of RFID readers are installed on the patrol location and the route passed by the inspector. Based on the complex environmental factors of the comprehensive pipe gallery and the reliability of the positioning system, in this paper, an improved RFID location algorithm is designed, which is based on the VIRE algorithm and the nonlinear spline interpolation method. The dynamic threshold is introduced to obtain the coordinates of the target position. Several groups of target positions, which are satisfying the conditions, are recorded and the average value is calculated as the final result. The experimental results show that the proposed algorithm is compared with the VIRE algorithm. The improved algorithm can reduce the location error from 0.368m to 0.161m. It has better localization effect and can be used to track and locate the patrol personnel of the comprehensive pipe gallery.

Robust Nonlinear Array Interpolation for Direction of Arrival Estimation of Highly Correlated Signals

Important signal processing techniques need that the response of the different elements of a sensor array have specific characteristics. For physical systems this often is not achievable as the array elements’ responses are affected by mutual coupling or other effects. In such cases, it is necessary to apply array interpolation to allow the application of ESPRIT, Forward Backward Averaging (FBA), and Spatial Smoothing (SPS). Array interpolation provides a model or transformation between the true and a desired array response. If the true response of the array becomes more distorted with respect to the desired one or the considered region of the field of view of the array increases, nonlinear approaches become necessary. This work presents two novel methods for sector discretization. An Unscented Transform (UT) based method and a principal component analysis (PCA) based method are discussed. Additionally, two novel nonlinear interpolation methods are developed based on the nonlinear regression schemes Multivariate Adaptive Regression Splines (MARS) and Generalized Regression Neural Networks (GRNNs). These schemes are extended and applied to the array interpolation problem. The performance of the proposed methods is examined using simulated and measured array responses of a physical system used for research on mutual coupling in antenna arrays.

Further improvement of weighted compact nonlinear scheme using compact nonlinear interpolation

To further improve the resolution of weighted compact nonlinear schemes(WCNS), a new 7th-order compact nonlinear interpolation method is proposed on the same stencil as 5th-order CRWENO scheme. Proper nonlinear weights are developed based on the Y type nonlinear weights, the properties of which are further analyzed in this paper. It is found that the Y type nonlinear weights are equivalent to the original nonlinear weights with an adaptive ϵ, which has very small value near discontinuities and very large value in smooth regions. As a result, the new nonlinear scheme has good shock capturing ability and achieves optimal order of accuracy in smooth regions. A new characteristic projection method is put forward, which largely reduces the computation costs. Simulations of Lax problem, Osher-Shu problem, double Mach reflection problem, decay of homogenous turbulence, shock turbulence interaction and turbulent channel flow show that the new scheme captures shocks without obvious oscillations, has higher resolution than other schemes tested, has obvious advantage in distinguishing turbulence from shocks and has higher efficiency.

Digital Modeling Phenomenon Of Surface Ground Movement

With the development of specialized software applications it was possible to approach and resolve complex problems concerning automating and process optimization for which are being used field data. Computerized representation of the shape and dimensions of the Earth requires a detailed mathematical modeling, known as "digital terrain model". The paper aims to present the digital terrain model of Vulcan mining, Hunedoara County, Romania. Modeling consists of a set of mathematical equations that define in detail the surface of Earth and has an approximate surface rigorously and mathematical, that calculated the land area. Therefore, the digital terrain model means a digital representation of the earth's surface through a mathematical model that approximates the land surface modeling, which can be used in various civil and industrial applications in. To achieve the digital terrain model of data recorded using linear and nonlinear interpolation method based on point survey which highlights the natural surface studied. Given the complexity of this work it is absolutely necessary to know in detail of all topographic elements of work area, without the actions to be undertaken to project and manipulate would not be possible. To achieve digital terrain model, within a specialized software were set appropriate parameters required to achieve this case study. After performing all steps we obtained digital terrain model of Vulcan Mine. Digital terrain model is the complex product, which has characteristics that are equivalent to the specialists that use satellite images and information stored in a digital model, this is easier to use.

An Image Sub-Pixel Edge Detection Algorithm of Plant Roots based on Non-linear Fourth-order Interpolation Method

To improve the accuracy of digital image edge detection, an ENO nonlinear fourth-order interpolation based subpixel edge detection algorithm was proposed in this paper. A stencil was constructed through classical Canny operator, followed by processing gray images to generate gradient images. ENO nonlinear fourth-order interpolation was applied in the gradient direction of target edges, and then subpixel subdivision computation was performed to obtain subpixel accurate locations of target edges, the performance of our edge detection algorithm was compared with that of centered cubic convolution and non-centered cubic convolution based edge detection methods. Simulation results demonstrated that the ENO based interpolation detection algorithm improved the abilities of detecting image edges.

An automatic video scratch removal based on Thiele type continued fraction

Old age, repeat play and improper preservation always deteriorate the film, and dust and mechanical operations produce artifacts like scratches and blotches. Many researches carried out to repair the damaged digital videos and video inpainting gradually becomes an important topic in digital image process ing. Challenges in scratched video inpainting are automatic detection of scratches and restoration of damaged part. This paper presents an automatic scratch detec tion method as well as a novel scratch removal approach. Stationary wavelet transform (SWT) which shows excellent performance in keeping translation-invariant is introduced to automatically detect the scratches, this strategy makes the scratches' detection more accurate. At the heart of our method is a new nonlinear interpolation method based on continued fraction in which Thiele-type continued fraction is used to interpolate surrounding known pixels for repairing the damaged part. Algorithm presented in this paper also utilizes both spatial and temporal information of the scratched video during the restoration stage. Experimental results show that our scheme not only obtains more accurate detection of scratches, but also gives better video quality.

Unified Approach for Notch Stress Strain Conversion Rules

There are several simplified methods, known as notch stress-strain conversion (NSSC) rules that provide an approximate formula to relate local elastic-plastic stresses and strains at the notch root to those estimated elastically. This paper investigates a unified approach that estimates nonlinear and history dependent stress-strain behavior of the notches using the conventional NSSC rules. A nonlinear interpolation method is adopted to estimate the elastic-plastic stress and strain at notches. A comparison is made between the finite element results for several notch configurations (with and without three-dimensional effects) and those obtained from NSSC rules and the proposed formulation.

Volumetric three-dimensional intravascular ultrasound visualization using shape-based nonlinear interpolation

BackgroundIntravascular ultrasound (IVUS) is a standard imaging modality for identification of plaque formation in the coronary and peripheral arteries. Volumetric three-dimensional (3D) IVUS visualization provides a powerful tool to overcome the limited comprehensive information of 2D IVUS in terms of complex spatial distribution of arterial morphology and acoustic backscatter information. Conventional 3D IVUS techniques provide sub-optimal visualization of arterial morphology or lack acoustic information concerning arterial structure due in part to low quality of image data and the use of pixel-based IVUS image reconstruction algorithms. In the present study, we describe a novel volumetric 3D IVUS reconstruction algorithm to utilize IVUS signal data and a shape-based nonlinear interpolation.MethodsWe developed an algorithm to convert a series of IVUS signal data into a fully volumetric 3D visualization. Intermediary slices between original 2D IVUS slices were generated utilizing the natural cubic spline interpolation to consider the nonlinearity of both vascular structure geometry and acoustic backscatter in the arterial wall. We evaluated differences in image quality between the conventional pixel-based interpolation and the shape-based nonlinear interpolation methods using both virtual vascular phantom data and in vivo IVUS data of a porcine femoral artery. Volumetric 3D IVUS images of the arterial segment reconstructed using the two interpolation methods were compared.ResultsIn vitro validation and in vivo comparative studies with the conventional pixel-based interpolation method demonstrated more robustness of the shape-based nonlinear interpolation algorithm in determining intermediary 2D IVUS slices. Our shape-based nonlinear interpolation demonstrated improved volumetric 3D visualization of the in vivo arterial structure and more realistic acoustic backscatter distribution compared to the conventional pixel-based interpolation method.ConclusionsThis novel 3D IVUS visualization strategy has the potential to improve ultrasound imaging of vascular structure information, particularly atheroma determination. Improved volumetric 3D visualization with accurate acoustic backscatter information can help with ultrasound molecular imaging of atheroma component distribution.