A NEW APPROACH FOR CONVERGENCE ACCELERATION OF ITERATIVE METHODS IN STRUCTURAL ANALYSIS

2013 ◽  
Vol 10 (04) ◽  
pp. 1350022 ◽  
Author(s):  
HAMED SAFFARI ◽  
ABDOLHOSSEIN BAGHLANI ◽  
NADIA M. MIRZAI ◽  
IMAN MANSOURI
Keyword(s):  
Nonlinear Analysis ◽  
Computational Cost ◽  
Convergence Acceleration ◽  
Equilibrium Path ◽  
New Approach ◽  
Performance Accuracy ◽  
Flow Algorithm ◽  
Newton Raphson ◽  
Low Computational Cost ◽  
Raphson Method

In this paper, a new approach is presented to accelerate the nonlinear analysis of structures with low computational cost. The method is essentially based on Newton–Raphson method, which has been improved in each iteration to achieve faster convergence. The normal flow algorithm has been employed to pass successfully through the limit points and through the entire equilibrium path. Subsequently, numerical examples are performed to demonstrate the efficiency of the formulation. The results show better performance, accuracy and rate of convergence of the present method to deal with nonlinear analysis of structures.

scholarly journals Features Determination from Super-Voxels Obtained with Relative Linear Interactive Clustering

2016 ◽  
Vol 21 (3) ◽  
pp. 69-79 ◽  
Author(s):  
Abdelkhalek Bakkari ◽  
Anna Fabijańska
Keyword(s):  
Computational Cost ◽  
Brain Images ◽  
3D Images ◽  
New Approach ◽  
Magnetic Resonance Imaging Mri ◽  
Ct Brain ◽  
Interactive Clustering ◽  
The Brain ◽  
Low Computational Cost ◽  
3D Magnetic Resonance Imaging

Abstract In this paper, the problem of segmentation of 3D Magnetic Resonance Imaging (MRI) and Computed Tomography (CT) brain images is considered. A supervoxel-based segmentation is regarded. In particular, a new approach called Relative Linear Interactive Clustering (RLIC) is introduced. The method, dedicated to image division into super-voxels, is an extension of the Simple Linear Interactive Clustering (SLIC) super-pixels algorithm. During RLIC execution firstly, the cluster centres and the regular grid size are initialized. These are next clustered by Fuzzy C-Means algorithm. Then, the extraction of the super-voxels statistical features is performed. The method contributes with 3D images and serves fully volumetric image segmentation. Five cases are tested demonstrating that our Relative Linear Interactive Clustering (RLIC) is apt to handle huge size of images with a significant accuracy and a low computational cost. The results of applying the suggested method to segmentation of the brain tumour are exposed and discussed.

An Efficient Power Flow Algorithm for Distribution Systems with Polynomial Load

2002 ◽  
Vol 39 (4) ◽  
pp. 371-386 ◽  
Author(s):  
Jianwei Liu ◽  
M. M. A. Salama ◽  
R. R. Mansour
Keyword(s):  
Power Flow ◽  
Distribution Systems ◽  
Test Results ◽  
Load Model ◽  
Voltage Ratio ◽  
Flow Algorithm ◽  
Convergence Control ◽  
Newton Raphson ◽  
Efficient Power ◽  
Raphson Method

A new, efficient power flow algorithm for complex distribution systems is presented. Voltage ratio is used for convergence control. This method has fast convergence ability for the polynomial load model for which the traditional Newton-Raphson method is usually not adaptable. Test results show the robustness of the proposed method.

scholarly journals Learning stable reduced-order models for hybrid twins

2021 ◽  
Vol 2 ◽  
Author(s):  
Abel Sancarlos ◽  
Morgan Cameron ◽  
Jean-Marc Le Peuvedic ◽  
Juliette Groulier ◽  
Jean-Louis Duval ◽  
...  
Keyword(s):  
Data Science ◽  
Time Integration ◽  
Computational Cost ◽  
Main Idea ◽  
Order Reduction ◽  
Machine Learning Techniques ◽  
Model Order ◽  
New Approach ◽  
Learning Techniques ◽  
Low Computational Cost

Abstract The concept of “hybrid twin” (HT) has recently received a growing interest thanks to the availability of powerful machine learning techniques. This twin concept combines physics-based models within a model order reduction framework—to obtain real-time feedback rates—and data science. Thus, the main idea of the HT is to develop on-the-fly data-driven models to correct possible deviations between measurements and physics-based model predictions. This paper is focused on the computation of stable, fast, and accurate corrections in the HT framework. Furthermore, regarding the delicate and important problem of stability, a new approach is proposed, introducing several subvariants and guaranteeing a low computational cost as well as the achievement of a stable time-integration.

scholarly journals Conflict Generalisation in ASP: Learning Correct and Effective Non-Ground Constraints

2020 ◽  
Vol 20 (5) ◽  
pp. 799-814
Author(s):  
RICHARD TAUPE ◽  
ANTONIUS WEINZIERL ◽  
GERHARD FRIEDRICH
Keyword(s):  
Computational Cost ◽  
Problem Instance ◽  
Test Cases ◽  
New Approach ◽  
Deductive Logic ◽  
Significant Performance ◽  
Speed Up ◽  
Problem Instances ◽  
Low Computational Cost ◽  
Additional Constraints

AbstractGeneralising and re-using knowledge learned while solving one problem instance has been neglected by state-of-the-art answer set solvers. We suggest a new approach that generalises learned nogoods for re-use to speed-up the solving of future problem instances. Our solution combines well-known ASP solving techniques with deductive logic-based machine learning. Solving performance can be improved by adding learned non-ground constraints to the original program. We demonstrate the effects of our method by means of realistic examples, showing that our approach requires low computational cost to learn constraints that yield significant performance benefits in our test cases. These benefits can be seen with ground-and-solve systems as well as lazy-grounding systems. However, ground-and-solve systems suffer from additional grounding overheads, induced by the additional constraints in some cases. By means of conflict minimization, non-minimal learned constraints can be reduced. This can result in significant reductions of grounding and solving efforts, as our experiments show.

scholarly journals Research on Oil and Gas Pipeline Operation Optimization Based on Improved Newton-Raphson Method

2021 ◽  
Vol 261 ◽  
pp. 01068
Author(s):  
Linjie Duan ◽  
Lipeng Zhang ◽  
Chunfeng Jiao ◽  
Rui Dang ◽  
Xudong Li ◽  
...  
Keyword(s):  
Oil And Gas ◽  
Computational Cost ◽  
Optimal Solution ◽  
Gas Pipeline ◽  
Programming Method ◽  
Mixed Integer ◽  
Pipeline System ◽  
Operation Optimization ◽  
Newton Raphson ◽  
Raphson Method

Oil and gas pipelines are the main channel to ensure national energy security and national economic development due to the safety and efficiency of the transportation coast. To achieve an optimal state of pipeline operation in terms of safety and efficiency is the crucial important issue throughout the life cycle of a pipeline system. However, the optimization problem of the pipeline network system is a typical Mixed Integer Non-Linear Problem (MINLP) which are extremely difficult to solve. An optimal solution to keep pipeline operated in most efficient state under the premise of safe operation is given in the paper by using the dynamical programming method. Firstly, the improved Newton-Raphson method is used to solve the discrete pipeline system, and the operating parameters such as temperature, pressure and flow of any section surface in the pipeline are obtained. The fluid parameter values of the each discrete nodes can ensure the safety of the pipeline. Based on this, the total energy consumption cost is set as the objective function, and the oil and gas pipeline operation optimization model is then established, and the dynamic programming method is used to solve it, so that it can obtain the optimal solution of the current working conditions in a reasonable computational cost. The actual example shows that the energy cost of the optimized operation scheme can be reduced by 6.8% compared with the pre-optimization scheme.

scholarly journals Improved Homotopy Perturbation Method for Geometrically Nonlinear Analysis of Space Trusses

2020 ◽  
Vol 10 (8) ◽  
pp. 2987
Author(s):  
Hamzeh Dehghani ◽  
Iman Mansouri ◽  
Alireza Farzampour ◽  
Jong Wan Hu
Keyword(s):  
Nonlinear Analysis ◽  
Geometrically Nonlinear ◽  
Nonlinear Load ◽  
Geometrically Nonlinear Analysis ◽  
Homotopy Perturbation ◽  
Perturbation Procedure ◽  
Numerical Computing ◽  
Newton Raphson ◽  
Space Trusses ◽  
Raphson Method

The objective of this study is to explore a noble application of the improved homotopy perturbation procedure bases in structural engineering by applying it to the geometrically nonlinear analysis of the space trusses. The improved perturbation algorithm is proposed to refine the classical methods in numerical computing techniques such as the Newton–Raphson method. A linear of sub-problems is generated by transferring the nonlinear problem with perturbation quantities and then approximated by summation of the solutions related to several sub-problems. In this study, a nonlinear load control procedure is generated and implemented for structures. Several numerical examples of known trusses are given to show the applicability of the proposed perturbation procedure without considering the passing limit points. The results reveal that perturbation modeling methodology for investigating the structural performance of various applications has high accuracy and low computational cost of convergence analysis, compared with the Newton–Raphson method.

An Iterative Numerical Method for Solving the Lane–Emden Initial and Boundary Value Problems

2018 ◽  
Vol 15 (04) ◽  
pp. 1850020 ◽  
Author(s):  
Mohamed Ben-Romdhane ◽  
Helmi Temimi
Keyword(s):  
Differential Equation ◽  
Numerical Simulation ◽  
Ordinary Differential Equation ◽  
Iterative Scheme ◽  
Computational Cost ◽  
Newton Raphson ◽  
Previous Iteration ◽  
Low Computational Cost ◽  
Unknown Solution ◽  
Quasilinearization Technique

In this paper, we propose fast iterative methods based on the Newton–Raphson–Kantorovich approximation in function space [Bellman and Kalaba, (1965)] to solve three kinds of the Lane–Emden type problems. First, a reformulation of the problem is performed using a quasilinearization technique which leads to an iterative scheme. Such scheme consists in an ordinary differential equation that uses the approximate solution from the previous iteration to yield the unknown solution of the current iteration. At every iteration, a further discretization of the problem is achieved which provides the numerical solution with low computational cost. Numerical simulation shows the accuracy as well as the efficiency of the method.

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