Electromagnetic scattering from electrically large objects with multiscale features is an increasingly important problem in computational electromagnetics. A conventional approach is to use an integral equation-based solver that is then augmented with an accelerator, a popular choice being a parallel multilevel fast multipole algorithm (MLFMA). One consequence of multiscale features is locally dense discretization, which leads to low-frequency breakdown and requires nonuniform trees. To the authors' knowledge, the literature on parallel MLFMA for such multiscale distributions capable of arbitrary accuracy is sparse; this paper aims to fill this niche. We prescribe an algorithm that overcomes this bottleneck. We demonstrate the accuracy (with respect to analytical data) and performance of the algorithm for both PEC scatterers and point clouds as large as 755 lambda with several hundred million unknowns and nonuniform trees as deep as 16 levels.

Accurate measurement of oil, water and gas flow without separation has always been a challenge in the oil and gas industry as it involves estimation of five different parameters. One of the critical parameters to estimate is Water-Cut (WC), which is the ratio of water flow rate to the total liquid flow rate. In this paper we employ microwave sensing techniques to measure WC. To establish the accuracy of microwave sensors for WC estimation a static mixer based approach is established with a ground truth accuracy of . Based on this ground truth the Water-Cut estimation accuracy is found to be ±1.5%. This paper is comprehensive summary of the experimental procedure, approach to estimate the uncertainty in reference Water-Cut and the performance of microwave sensors in estimating Water-Cut.

Accurate and reliable measurement of oil, gas and water flow rates as they flow along a pipe as a mixture continues to be a challenging problem in the oil and gas industry. Most of the solutions rely on radioactive sources. This paper explores the use of microwave sensors for flow rate measurement. Microstrip Patch sensors in transmission mode and a near field coaxial probe in reflection mode are used to estimate water fraction even in lossy (saline) medium using physics based models with minimal calibration. Reflection measurements from the Patch sensors are used to estimate gas fraction using empirical models which can enable measurement of gas in high loss cases. Gas velocity is measured from cross correlation. A low cost 5-port measuring instrument was built to do reliable reflection and transmission measurements over a wide temperature range. The microwave system was tested in in-house and external flow loops and in the field under varying temperatures and flow conditions and test results are presented in this paper.

The development of the multilevel fast multipole algorithm (MLFMA) and its multiscale variants have enabled the use of integral equation (IE) based solvers to compute scattering from complicated structures. Development of scalable parallel algorithms, to extend the reach of these solvers, has been a topic of intense research for about a decade. In this paper, we present a new algorithm for parallel implementation of IE solver that is augmented with a wideband MLFMA and scalable on large number of processors. The wideband MLFMA employed here, to handle multiscale problems, is a hybrid combination of the accelerated Cartesian expansion (ACE) and the classical MLFMA. The salient feature of the presented parallel algorithm is that it is implicitly load balanced and exhibits higher performance. This is achieved by developing a strategy to partition the MLFMA tree, and hence the associated computations, in a self-similar fashion among the parallel processors. As detailed in the paper, the algorithm employs both spatial and direction partitioning approaches in a flexible manner to ensure scalable performance. Plethora of results are presented here to exhibit the scalability of this algorithm on 512 and more processors.

Fast multipole methods (FMM) and their immediate predecessors, tree codes, were developed in response to the need for solving N-body problems that occur in applications as varied as biophysics, computational chemistry, astrophysics and electromagnetics. In all these areas, it is necessary to compute long range potentials of the form 1/R between a dense distribution of point charges, where R is the distance between any two charges. Often, repeated evaluation of these potentials is necessary. It is apparent that the cost of direct evaluation, which scales as O(N-2) for N degrees of freedom, forms a fundamental bottleneck. FMM and tree methods ameliorate the cost associated with these computation; CPU times of these method scale as O(N). It stands to reason that FMM has had a seminal impact on a multitude of fields, so much so, that it was recognized as one of the top ten algorithms of the past century. A method to rapidly compute potentials of the form e(-jkR)/R soon followed. As the reader is aware, these potentials are the crux of integral equation based analysis tools in electromagnetics and the advent of these methods have transformed the face of computational electromagnetics. Consequently, the state of art of integral equation solvers has grown by leaps and bounds over the past decade. This paper attempts to present a detailed review of the state of art of FMM based methods that are used in computational electromagnetics, from the static to the high frequency regime.

Multiscale electromagnetic simulations contain features with multiple length or frequency scales or both. Multiscale features are characteristic of realitic simulations as large degrees of freedom (N) are required to capture the minute physical details. Though integral equation (IE) approaches are well-suited for electromagnetic simulations, they require repeated evaluation of pair-wise potentials - also referred to as N-body problems. It is well known that the direct computation of these potentials scales as O (N2) both in terms of computer memory and time. Even with the rapid advancements in computer technology, this places severe limitation on the size of the problem (N) that can be analyzed in a realistic time frame. Further, multiscale simulations produce badly-conditioned systems of equations that require large number of iterations when using Krylov-subspace solvers. The main goal of this thesis is to develop a suite of computational techniques that enables multiscale electromagnetic simulations in a fast, efficient and stable fashion. In this work, the accelerated Cartesian expansion (ACE) algorithm is used to overcome the quadratic cost-scaling of N-body problems. ACE was intially developed for the fast evaluation of polynomial potentials and here it is extended to the fast computation of retarded and Helmholtz potentials. These algorithms are shown to be stable and efficient for computation of electromagnetic potentials at sub-wavelength or low-frequency scales. Hybrid combination of these algorithms with existing fast methods leads to the development of multiscale electromagnetic solvers that are stable and efficient across length and frequency scales. Since the fast algorithms only reduce the time spent in each iteration, a new integral equation formulation is developed that yields better conditioned systems of equations. This is achieved by reformulating the augmented field integral equations such that the resulting operators are bounded and compact. Further, the widespread availability of parallel distributed or cluster computers combined with the memory and speed restriction of single processor computers necessitates the development of efficient parallel implementation of the sophisticated fast algorithms. The parallel algorithms developed in this work are provably scalabale and enables simulation of problems with several millions of unknowns on large scale clusters, with hundreds of processors and beyond. In this thesis, ACE algorithm is also extended to rapid computation of time domain diffusion potentials.

In this paper, we propose a novel scheme to accelerate integral equation solvers when applied to multiscale problems. These class of problems exhibit multiple length/frequency scales and arise when analyzing scattering/radiation from realistic structures where dense discretization is necessary to accurately capture geometric features. Solutions to the discretized integral equations due to these structures is challenging, due to their high computational cost and ill-conditioning of the resulting matrix system. The focus of this paper is on ameliorating the computational cost. Our approach will rely on exploiting the recently developed accelerated Cartesian expansion (ACE) algorithm to arrive at a method that is stable and efficient at low frequencies. These will then be integrated with the well known fast multipole method, thus forming a scheme that is wideband. Rigorous convergence estimates of this method are derived, and convergence and efficiency of the overall fast method is demonstrated. These are then integrated into an existing integral equation solver, whose efficiency is demonstrated for some practical problems.

Short-pulsed terahertz imaging techniques have found application in recent years especially in the areas of nondestructive evaluation, homeland security and biomedical imaging. One such application involves the inspection of bonding between spray on foam insulation (SOFI) and the external tank in the NASA space shuttle. This work discusses a suite of image enhancement techniques that was developed to improve the probability of detection of voids and disbands SOFI. Physics based defect detection and profiling methods are detailed along with initial results. In addition a ray-tracing model was developed to simulate the inspection process. Results comparing the model and experimental images will also be presented.

Onsite real-time nondestructive evaluation of aircraft using eddy current techniques has gained significance in the past few years. In this paper, emphasis is placed on developing a flexible and a fast real-time inspection system using giant magnetoresistive (GMR) field sensors. Experimental signals are compared with finite-element model (FEM) model simulations and signals acquired using traditional data acquisition methods. Several advantages of the improved design are discussed.

Views Icon Views Article contents Figures & tables Video Audio Supplementary Data Peer Review Share Icon Share Twitter Facebook Reddit LinkedIn Tools Icon Tools Reprints and Permissions Cite Icon Cite Search Site Citation Vikram R. Melapudi, Lalita Udpa, Satish S. Udpa, William P. Winfree; Ray‐Rracing Model for Terahertz Imaging of SOFI Inspection. AIP Conf. Proc. 6 March 2006; 820 (1): 477–483. https://doi.org/10.1063/1.2184566 Download citation file: Ris (Zotero) Reference Manager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex toolbar search Search Dropdown Menu toolbar search search input Search input auto suggest filter your search All ContentAIP Publishing PortfolioAIP Conference Proceedings Search Advanced Search |Citation Search