Local Adaptive Method Research Articles

Adaptive Mesh Refinement and Probe Signal Calculation in Eddy Current NDT by Complementary Formulations

A local error estimation and adaptive meshing method for finite element analysis in eddy current nondestructive testing problems is proposed. Two dual formulations using Whitney elements have been applied to solve the magnetodynamic problem. By using this property of complementary, different error estimators were defined and were studied. These estimators are used for determining the mesh refinement zones. Numerical evaluations are given at the end of the paper, where the procedure of the adaptive meshing is presented and validated.

HDR image compression and evaluation based on local adaptation using a retinal model

Abstract— The retinal adaptation process helps the human visual system to see high‐dynamic‐range (HDR) scenes in the real world. A simple static local adaptation method for HDR image compression based on a retinal model is presented. The proposed simple model aims at recreating the same sensations of the human visual system between the real‐world scene and the range compressed image on the display device when viewed after the human visual system reaches the steady local adaptation state, respectively. In computing scene local adaptation, the use of a non‐linear edge‐preserving bilateral filter not only presents a better tonal rendition in compressing local contrast and preserving details but also avoids banding artifacts across high‐gradient edges. Our new model relates the display adaptation with the scene adaptation based on the retinal model. In order to verify the effectiveness, a subjective evaluation is made by comparing the real scene and the display image using the paired comparison technique.

Development of a local MQ‐DQ‐based stencil adaptive method and its application to solve incompressible Navier–Stokes equations

AbstractIn this paper, a local stencil adaptive method is presented, which is designed for solving computational fluid dynamics (CFD) problems with curved boundaries accurately. A local multiquadric‐differential quadrature (MQ‐DQ) method is used to discretize the governing equations, taking advantage of its meshless nature. The present method bears the properties of both local MQ‐DQ method and local stencil adaptive method and is thus named the local MQ‐DQ‐based stencil adaptive method. Two test problems with curved boundaries are solved to investigate the performance of this solution‐adaptive method. The numerical results indicate that the proposed method is effective and efficient by combining the advantages of meshless property for complex geometries and local adaptation for accuracy improvement. Copyright © 2007 John Wiley & Sons, Ltd.

HDR Image Compression by Local Adaptation for Scene and Display Using Retinal Model

Adaptation process of retina helps human visual system to see a high dynamic range scene in real world. This paper presents a simple static local adaptation method for high dynamic range image compression based on a retinal model. The proposed simple model aims at recreating the same sensations between the real scene and the range compressed image on display device when viewed after reaching steady state local adaptation respectively. Our new model takes the display adaptation into account in relation to the scene adaptation based on the retinal model. In computing local adaptation, the use of nonlinear edge preserving bilateral filter presents a better tonal rendition in preserving the local contrast and details while avoiding banding artifacts normally seen in local methods. Finally, we demonstrate the effectiveness of the proposed model by estimating the color difference between the recreated image and the target visual image obtained by trial and error method.

A moving mesh interface tracking method for 3D incompressible two-phase flows

An interface tracking method using an unstructured moving mesh has been developed for simulating three-dimensional, incompressible, and immiscible two-phase flows. The interface mesh is moved in a Lagrangian fashion. A local mesh adaptation method is used to capture the changing interface curvature, maintain good mesh quality, and deal with large deformation. The interface is of zero thickness, so the jump and continuity conditions across the interface are implemented directly, without any smoothing of the properties of the two fluids. This is theoretically beneficial compared to other methods that allow the fluids’ properties to continuously vary in an interface region. The curvature for interfacial tension calculation is geometrically computed by a least squares parabola fitting method. A mesh separation scheme for interfacial flows is employed to handle topological transition. The numerical technique is tested and validated by several cases, which include a two-layer Couette flow, an oscillating droplet surrounded by gas, and a droplet in shear flow. The results obtained from numerical simulations are found to be in excellent agreement with analytical solutions and experimental results. A collapsing ligament in a quiescent gas flow and a modulated jet pinching are simulated to show the robustness of the method.

A novel multi-step adaptive prediction method for chaotic time series

Based on the short-term predictability of chaotic time series and the adaptive tracking chaotic trajectory of adaptive algorithm, a novel multi-step adaptive prediction method is proposed in this paper to resolve the problem of adjusting the filter parameters of the local adaptive prediction method during multi-step prediction. Simulation results show that this multi-step adaptive prediction method can be successfully used to make multi-step predictions, and its performance is better than that of the local adaptive prediction algorithm.

Adaptive Perception With Locally Adaptable Sensor Array

In this paper, we propose some biologically motivated local image-sensor adaptation methods. The special feature of these methods is, that they change the integration time of the imager on the pixel level. Using these methods, low dynamic-range integration type CMOS sensors will be able to perceive high dynamic-range scenes, and at the same time, compress their dynamic range by keeping high contrast and without introducing nonexisting edges.

Local adaptive methods for convection dominated problems

AbstractIn this paper, we consider rigorous a posteriori error estimates for convection dominated initial value problems including recent results for those with degenerating diffusion. These estimates are important to control the adaptive local mesh refinement for numerical computations, in particular for the simulation of the biodegradation process. Several results obtained by numerical experiments will be shown. Copyright © 2002 John Wiley & Sons, Ltd.

Error estimation and adaptive meshing in 3D electrostatic and magnetostatic problems

A local error estimation and adaptive meshing method developed by some of the authors for finite element analysis of 2D electrostatic and magnetostatic problems is now extended to 3D problems. The problems are formulated in terms of scalar potentials and discretized on a tetrahedral mesh using linear shape functions. Local error is estimated by approximately solving an independent differential problem in each tetrahedral element. The elements selected for refinement are subdivided by adding nodes inside the element, or along an edge, depending on their geometrical quality factor.

The sustainable intensification of agriculture

Agricultural development is currently facing unprecedented challenges. With 800 million people already having insufficient access to food, population growth estimates project an even bleaker situation in the future. The article summarizes the major schools of thought regarding how to face the dilemma, and advocates sustainable intensification of agriculture, relying on integrated use of a wide range of technologies to manage pests, nutrients, soil and water. Local knowledge and adaptive methods are stressed rather than comprehensive packages of externally‐supplied technologies. The article shows how regenerative, low‐input agriculture, founded on full farmer participation in all stages of development and extension, can be highly productive. It is stressed that policy must not prescribe specific, concretely defined technologies or practices, as this would restrict future farmer options. Farmers and communities should be allowed and encouraged to adapt to changing conditions; what needs to be sustainable are local processes of innovation and adaptation.The article highlights environmental and economic benefits resulting from sustainable intensification practices, for farmers as well as communities and nations with examples are taken from Africa, Asia and Latin America.Despite the increasing success of sustainable agriculture, it is clear that the challenge remains to ‘scale up’ the process from small ‘islands of success’ to fundamental reform of both policies and policy formulation processes.

Mesh adaptation in finite element analysis of 2D steady state time harmonic eddy current problems

A local error estimation and adaptive meshing method developed by the authors for finite element analysis of 2D electrostatic and magnetostatic problems is now extended to 2D steady state time harmonic quasistatic eddy current problems. Local error estimation is based on the approximate solution of an independent differential problem in each triangular element. Mesh refinement is carried out by adding nodes in the centroids of selected elements and then applying the Delaunay algorithm.

Nonstationary analysis by bpes (backward prediction error space)

AbstractThis paper describes a method of non‐stationary analysis based on the geometrical orthogonal projection with least‐squares estimation for a linear model. In the past, local stationary analysis and adaptive methods which successively estimate the parameters have been used for this purpose. However, in application to the nonstationarity case as in biomedical signals these methods have the disadvantage that it is difficult to see the physical significance of the parameters. In consideration of this, the present paper defines the backward prediction error space (BPES) consisting of the backward prediction error vector in each dimension and proposes to handle the nonstationarity by expanding the property into the orthogonal states in each dimension. The backward prediction error vectors constitute an orthogonal system in the least‐squares estimation and the reflection coefficient is the parameter directly related to this system. The orthogonality can be interpreted in direct relation to the independence of physical functions. As a measure of the nonstationarity, the angle between the vectors is adopted in the BPES. When the parameters which were optimum in the stationary interval are applied to an arbitrary interval, the angle is an exact expression of the discrepancy due to the nonstationarity. By an example of analysis of biomedical signals it is verified that the angle is useful in evaluation of the nonstationarity, especially of that arising from the change of orders. Thus, it is anticipated that the deterministic nonstationary analysis by BPES will provide new information about biological systems.