1,721,088 research outputs found
A Volume PEEC Formulation Based on the Cell Method for Electromagnetic Problems from Low to High Frequency
No full textA new and general partial element equivalent circuit (PEEC) formulation based on electric and magnetic vector potentials and the cell method is presented. The purpose of this paper is manifold. First, a comprehensive review of wellestablished PEEC method is given and the state-of-the-art of the method with focus on the inclusion of magnetic media in the formulation is discussed. Then, a new and general formulation of the PEEC method based on integral equations is proposed. The formulation is valid for conductive, dielectric, and magnetic media and its advantages with respect to the state-of-the-art PEEC formulations are underlined. Unlike the existing PEEC methods, this novel formulation, thanks to the reinterpretation of PEEC in the context of integral equation methods, allows for maintaining a circuit interpretation for both electric and magnetic media. Thus, a standard Spice-like solver can in principle be adopted for the solution of electromagnetic (EM) problems also when magnetic media are involved. The imposition of the divergence condition for the current density vectors is guaranteed and also the case of inhomogeneous and anisotropic media is considered. A thorough discussion on the suitability of the method for the study of both low- and high-frequency EM problems is also presented. Finally, the case study of a near-field communication antenna is considered as an example of the applicability of the formulation to problems of industrial interest. Comparisons with commercial softwares, measurements, and the state-of-the-art PEEC method are given in order to demonstrate the accuracy and the advantages of the proposed PEEC formulation
Integral Equation-Based Topology Optimization of an EMI Filter
No full textTopology Optimization (TO) stands as a powerful instrument for elevating the design paradigm of electromagnetic devices, particularly with the integration of advanced additive manufacturing methodologies. Through the coupling of the integral equation method and binary Topology Optimization, a tool is proposed for the purposeful design of filters tailored to efficaciously mitigate Electromagnetic Interference (EMI)
Comparative Analysis of Hierarchical Matrix Formats for Electromagnetic Device Modeling: A Preliminary Study
No full textThis paper investigates the performance of three hierarchical matrix (H-matrix) formats for modeling electromagnetic devices using the Electric Field Integral Equation (EFIE) and the Augmented EFIE (A-EFIE) formulation. These methods are applied to a benchmark problem, the single-ended microstrip transmission line, to evaluate their efficiency in terms of memory usage and accuracy
Hierarchical Matrices Accelerated Topology Optimization of Patch Antenna
No full textIntegral equation method-based topology optimization (IEM-TO) may result in excessive computational burden due to the fully populated matrices generated during the discretization process. To extend the applicability of IEM-TO to large-scale problems, with many degrees of freedom, hierarchical matrices (H-matrices) can be used to drastically reduce the overall computational burden. Exploiting this concept, high-resolution topologies can be obtained at the end of the optimization process
Portable system for fast lung function test
No full textThe analysis of gas-concentration changes at mouth during normal breathing is nowadays a routine exam to infer the lung functionality and several commercial instruments are available to carry out this kind of measurements. Unfortunately, most of these measuring systems are very specific, designed to be used in the hospital and costly. This paper describes a complete and versatile system which is designed for in the field use and can be tailored to several different measurement situations. The proposed system employs commercial sensors coupled to a versatile conditioning and acquisition board, which is designed to be connected to a conventional Personal Computer. A skeleton of a software which carries out the routine tasks (acquisition, storing, calibrations, and visualization) has been designed and installed on the PC. The skeleton can be easily adapted to the different applications, thus enabling the fast development of new clinical methodics. As an example, in this paper, an application is described that performs an Oxygen/Carbon-Dioxide analysis on a multi-breath basis and estimates the result uncertainty. The skeleton contains routines to save both results and raw data according to the Digital Imaging and Communication in Medicine (DICOM) standard format, so that the analyzes can be easily shared among the different physicians involved in the patient's care
Evaluation of surgical risks by means of neural networks in the presence of uncertainties
No full textSurgical risks in elderly patients are often rather high and therefore a need exists for preoperative tests that are able to predict the postoperative risk of mortality. In most cases no test has been found to be completely able to predict postoperative severe complications although reasonable results can be obtained by employing a multi-test approach. A neural network can conveniently be employed to perform the required data-fusion thus producing an overall "risk index"; however the surgical outcome being of a binary type, the network output tends to be a step-like function that does not give much information on the risk level. In this paper a modified training approach that takes the parameter uncertainties into account and which trains the network avoiding the step-like behaviour is proposed. The results that can be obtained with this approach are eventually explained by applying it to the estimation of a surgical risk index for lung resection procedures in patients affected by lung cance
Uncertainty Analysis of Feature Extraction from Expired Gas Traces
Full text linkNoninvasive medical analyses are a convenient method to study several pathologies even though their indirect nature often requires a complex processing to determine the relevant health "indicators". The usefulness of such indicators depends on the employed model, but also on the uncertainty that is connected to the complex processing involved in the indicator determination. This paper deals with the problems related to the estimation of the uncertainty when the indicators are computed by means of a nontrivial processing on recorded traces of clinical parameters. The paper is focused on the analysis of expired gas traces, but the procedure can also be applied to many other cases where the processing involves manual or automatic selection of suitable "key points" on repetitive traces
Gradient-Informed Weighted Sum Multi-Objective Topology Optimization in Electromagnetics
No full textMixed Neural-Conventional Processing to Differentiate Airway Diseases by Means of Functional Noninvasive Tests
Full text linkThis paper describes a processing technique that can be used to combine information from different medical analyze to discriminate between different pathologies that have similar symptoms. The paper is focused on the differentiation between asthma, bronchitis, and emphysema, using only functional noninvasives tests, but the proposed technique can be easily applied to other similar situations where different tests have to be used to identify a pathology. The technique is based on mixed neural-and-conventional processing that not only suggests the pathology, but also estimates the reliability of this suggestion
Gradient-Informed Pareto-Based Multi-Objective Binary Topology Optimization
Full text linkMulti-objective topology optimization (TO) problems frequently arise in practical engineering applications, necessitating the identification of Pareto-optimal solutions. This article introduces a gradientin-formed Pareto-based multi-objective TO algorithm with binary decision variables, called GPBTO, tailored to constrained bi-objective optimization problems (CBOPs), a common scenario in engineering design. By leveraging a binary decision space and incorporating a linearization step for objectives and constraints, the method enables the use of efficient integer linear programming (ILP) techniques for evolving the decision vector. Unlike traditional weighted sum (WS) approaches, which are widely used in TO despite their known limitations, GPBTO provides an alternative that integrates gradient-based formulations while facilitating the identification of Pareto-optimal solutions. While WS remains a dominant method in TO, GPBTO represents a promising alternative for cases where Pareto-based..
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