scholarly journals Iterative MLFMA-MADBT Technique for Analysis of Antenna Mounted on Large Platforms

2020 ◽  
Vol 11 (1) ◽  
pp. 148
Author(s):  
Mingjie Pang ◽  
Han Wang ◽  
Hai Lin
Keyword(s):  
High Frequency ◽  
Large Scale ◽  
Asymptotic Methods ◽  
Hybrid Technique ◽  
Radiation Patterns ◽  
Time Consumption ◽  
The Matrix ◽  
Multi Level ◽  
Fast Multipole Algorithm ◽  
Matrix Vector

A hybrid technique combining the multi-level fast multipole algorithm (MLFMA) and the modified adaptive division beam tracing (MADBT) is presented to analyze the radiation patterns of the antennas mounted on large-scale complex platforms. In this technique, the MLFMA is used to characterize the antenna and the transition region that cannot be analyzed accurately by high-frequency asymptotic methods. The MADBT method is used to analyze the contribution of the platforms to the entire radiation pattern by tracing all beams effectively. By applying the beam-based MADBT method instead of the conventional current-based physical optics (PO) method to the platforms, the multi-bounce effects inside the platforms are considered, which enhances the accuracy of the radiation patterns, especially for the complex platforms with corner reflector. An iteration method is proposed to model the interaction between the antennas and the platforms strictly. The proposed iterative MLFMA-MADBT method is mesh-independent and can avoid the matrix-vector production (MVP) of the iterative MLFMA-PO method in each iteration. These characters significantly reduce the memory and time consumption in computation while keeping high accuracy. Numerical results are presented to demonstrate the accuracy and efficiency of the proposed hybrid technique.

scholarly journals Improved Generalized Single-Source Tangential Equivalence Principle Algorithm with Contact-Region Modeling Method for Array Structures

2018 ◽  
Vol 2018 ◽  
pp. 1-11
Author(s):  
Yao Han ◽  
Hanru Shao ◽  
Jianfeng Dong
Keyword(s):  
Equivalence Principle ◽  
Contact Region ◽  
Near Field ◽  
Single Source ◽  
Matrix Vector Multiplication ◽  
The Matrix ◽  
Array Structures ◽  
Fast Multipole Algorithm ◽  
Matrix Vector ◽  
Equivalence Principle Algorithm

An improved generalized single-source tangential equivalence principle algorithm (GSST-EPA) is proposed for analyzing array structures with connected elements. In order to use the advantages of GSST-EPA, the connected array elements are decomposed and computed by a contact-region modeling (CRM) method, which makes that each element has the same meshes. The unknowns of elements can be transferred onto the equivalence surfaces by GSST-EPA. The scattering matrix in GSST-EPA needs to be solved and stored only once due to the same meshes for each element. The shift invariant of translation matrices is also used to reduce the computation of near-field interaction. Furthermore, the multilevel fast multipole algorithm (MLFMA) is used to accelerate the matrix-vector multiplication in the GSST-EPA. Numerical results are shown to demonstrate the accuracy and efficiency of the proposed method.

Inplementation of an Efficient Parallel Multilevel Fast Multipole Algorithm

2012 ◽  
Vol 433-440 ◽  
pp. 4268-4272
Author(s):  
You Feng Chen ◽  
Dong Lin Su ◽  
Xiao Ying Zhao ◽  
Dan Dan Guo ◽  
Li Peng Deng
Keyword(s):  
Shared Memory ◽  
High Frequency ◽  
Large Scale ◽  
Memory System ◽  
Method Of Moment ◽  
Fast Multipole ◽  
Multilevel Fast Multipole Algorithm ◽  
Shared Memory System ◽  
Fast Multipole Algorithm

This paper is concerned with the implementation of the parallel multilevel fast multipole algorithm(MLFMA) for large scale electromagnetics simulation on shared-memory system. The algorithm is implemented on a method of moment discretisation of the electromagnetics scattering problems.The developed procesure is validated by compared to benchmarks defined by Electromagnetics Code Consortium(EMCC) .The procesure can evaluate large problemssuch as electromagnetics scattering of aircraft at high-frequency with up to several millions of unknowns.

Acceleration of the calculations for solving large problems using the boundary element method for the Stokes equations on GPU

2011 ◽  
Vol 8 (1) ◽  
pp. 189-197
Author(s):  
O.A. Solnyshkina
Keyword(s):  
Boundary Element Method ◽  
Boundary Element ◽  
Large Scale ◽  
Stokes Equations ◽  
Fluid Motion ◽  
Creeping Flow ◽  
Graphics Processors ◽  
The Matrix ◽  
Matrix Vector ◽  
Element Method

A creeping flow of a viscous fluid in a channel in 3D formulation is considered. The fluid motion is described by the Stokes equations. The problem is solved numerically using the boundary element method. The obtained results are compared with the analytical solution. To accelerate the calculations for solving large-scale problems, the software component of the matrix-vector product is developed and parallelized on the graphics processors. The paper presents the results of the GPU utilization for the considered problems.

scholarly journals Efficient and Memory Saving Method Based on Pseudoskeleton Approximation for Analysis of Finite Periodic Structures

2018 ◽  
Vol 2018 ◽  
pp. 1-6
Author(s):  
Chunbei Luo ◽  
Yong Zhang ◽  
Hai Lin
Keyword(s):  
Periodic Structures ◽  
Function Analysis ◽  
Computation Time ◽  
Analysis Model ◽  
Accurate Analysis ◽  
Periodic Property ◽  
The Matrix ◽  
Memory Resources ◽  
Fast Multipole Algorithm ◽  
Matrix Vector

An efficient and memory saving method based on pseudoskeleton approximation (PSA) is presented for the effective and accurate analysis of finite periodic structures. Different from the macro basis function analysis model, our proposed method uses the formulations derived by the local Rao-Wilton-Glisson basis functions. PSA is not only used to accelerate the matrix-vector product (MVP) inside the single unit but also adopted to decrease the calculation burden of the coupling between the different cells. Moreover, the number of decomposed coupling matrices is minimized due to the displacement invariance of the periodic property. Consequently, even compared with the multilevel fast multipole algorithm (MLFMA), the new method saves much more memory resources and computation time, which is also demonstrated by the numerical examples.

A Novel Iteration Model for Electromagnetic Scattering from Rough Surfaces

Frequenz ◽  
2016 ◽  
Vol 70 (1-2) ◽  
Author(s):  
Chang-Ze Li ◽  
Chuangming Tong ◽  
Lihui Qi ◽  
Weijie Wang ◽  
An Wang
Keyword(s):  
Electromagnetic Scattering ◽  
Large Scale ◽  
Rough Surfaces ◽  
Scattering Problem ◽  
Field Approximation ◽  
The Matrix ◽  
Iteration Model ◽  
Randomly Rough Surfaces ◽  
Matrix Vector ◽  
Relaxation Iteration

AbstractAn iterative physical optics (IPO) is proposed to solve the extra large scale (e.g. larger than one thousand square lambda) electromagnetic (EM) scattering from randomly rough surfaces in this paper. The forward-backward methodology and its modification with under-relaxation iteration improve convergence and stability of the IPO; the fast far-field approximation (FaFFA) in the matrix-vector product reduces the computational complexity based on the scattering characteristics of rough surface. Through these techniques, this model can solve effectively the extra large scale scattering problem from the randomly rough surfaces.

scholarly journals ANALYSIS OF COMPOSITE DIELECTRIC METAMATERIALS USING INTEGRAL EQUATION TECHNIQUES

2020 ◽  
Author(s):  
John Stevenson
Keyword(s):  
Integral Equation ◽  
Method Of Moments ◽  
Electromagnetic Scattering ◽  
Three Dimensional ◽  
Surface Integral ◽  
Integral Equation Formulation ◽  
The Matrix ◽  
Speed Up ◽  
Fast Multipole Algorithm ◽  
Matrix Vector

We study numerically the electromagnetic scattering properties of three dimensional (3D),arbitrary shaped composite dielectric metamaterials. Using integral equation techniques, we firstderive a surface integral equation formulation which produces well-conditioned matrix equation.To solve the obtained integral equations, we apply a Galerkin scheme and choose the basis andtesting functions as Rao-Wilton-Glisson defined on planar patches. We then develop an algorithmto speed up the matrix-vector multiplications by employing the well-known method of moments(MoM) and the multilevel fast multipole algorithm on personal computer (PC) clusters. Some 3Dnumerical examples are presented to demonstrate the validity and accuracy of the proposedapproach.

The three paradoxes of the energy transition - Assessing sustainability of large-scale solar photovoltaic through multi-level and multi-scalar perspective in Rwanda

2021 ◽  
Vol 288 ◽  
pp. 125519
Author(s):  
Carole Brunet ◽  
Oumarou Savadogo ◽  
Pierre Baptiste ◽  
Michel A. Bouchard ◽  
Céline Cholez ◽  
...  
Keyword(s):  
Large Scale ◽  
Energy Transition ◽  
Solar Photovoltaic ◽  
Multi Level

scholarly journals Synthesis of Metal Organic Frameworks by Ball-Milling

Crystals ◽  
2020 ◽  
Vol 11 (1) ◽  
pp. 15
Author(s):  
Cheng-An Tao ◽  
Jian-Fang Wang
Keyword(s):  
Ball Milling ◽  
Large Scale ◽  
Raw Materials ◽  
Metal Organic Frameworks ◽  
Research Topic ◽  
Mass Ratio ◽  
Time Consumption ◽  
Metal Organic ◽  
Short Time ◽  
Made In

Metal-organic frameworks (MOFs) have been used in adsorption, separation, catalysis, sensing, photo/electro/magnetics, and biomedical fields because of their unique periodic pore structure and excellent properties and have become a hot research topic in recent years. Ball milling is a method of small pollution, short time-consumption, and large-scale synthesis of MOFs. In recent years, many important advances have been made. In this paper, the influencing factors of MOFs synthesized by grinding were reviewed systematically from four aspects: auxiliary additives, metal sources, organic linkers, and reaction specific conditions (such as frequency, reaction time, and mass ratio of ball and raw materials). The prospect for the future development of the synthesis of MOFs by grinding was proposed.

Da eine oder mehrere betroffen …

2020 ◽  
Vol 48 (1) ◽  
pp. 47-100
Author(s):  
Melitta Gillmann
Keyword(s):  
High Frequency ◽  
Formal Language ◽  
Subordinate Clause ◽  
Matrix Clause ◽  
Very High Frequency ◽  
Corpus Study ◽  
Causal Relations ◽  
Legal Texts ◽  
The Matrix ◽  
Very High

AbstractBased on a corpus study conducted using the GerManC corpus (1650–1800), the paper sketches the functional and sociosymbolic development of subordinate clause constructions introduced by the subjunctor da ‘since’ in different text genres. In the second half of the 17th and the first half of the 18th century, the da clauses were characterized by semantic vagueness: Besides temporal, spatial and causal relations, the subjunctor established conditional, concessive, and adversative links between clauses. The corpus study reveals that different genres are crucial to the readings of da clauses. Spatial and temporal usages, for example, occur more often in sermons than in other genres. The conditional reading, in contrast, strongly tends to occur in legal texts, where it displays very high frequency. This could be the reason why da clauses carry indexical meaning in contemporary German and are associated with formal language. Over the course of the 18th century, the causal usages increase in all genres. Surprisingly, these causal da clauses tend to be placed in front of the matrix clause despite the overall tendency of causal clauses to follow the matrix clause.

Selecting optimal SpMV realizations for GPUs via machine learning

2021 ◽  
pp. 109434202199073
Author(s):  
Ernesto Dufrechou ◽  
Pablo Ezzatti ◽  
Enrique S Quintana-Ortí
Keyword(s):  
Machine Learning ◽  
Sparse Matrix ◽  
Machine Learning Techniques ◽  
Optimal Method ◽  
Learning Techniques ◽  
General Rules ◽  
Machine Learning Approach ◽  
The Matrix ◽  
Time And Energy ◽  
Matrix Vector

More than 10 years of research related to the development of efficient GPU routines for the sparse matrix-vector product (SpMV) have led to several realizations, each with its own strengths and weaknesses. In this work, we review some of the most relevant efforts on the subject, evaluate a few prominent routines that are publicly available using more than 3000 matrices from different applications, and apply machine learning techniques to anticipate which SpMV realization will perform best for each sparse matrix on a given parallel platform. Our numerical experiments confirm the methods offer such varied behaviors depending on the matrix structure that the identification of general rules to select the optimal method for a given matrix becomes extremely difficult, though some useful strategies (heuristics) can be defined. Using a machine learning approach, we show that it is possible to obtain unexpensive classifiers that predict the best method for a given sparse matrix with over 80% accuracy, demonstrating that this approach can deliver important reductions in both execution time and energy consumption.

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