Equivalent cable harness method generalized for predicting the electromagnetic emission of twisted-wire pairs

Introduction. In this paper, the equivalent cable harness method is generalized for predicting the electromagnetic emissions problems of twisted-wire pairs. The novelty of the proposed work consists in modeling of a multiconductor cable, in a simplified cable harness composed of a reduced number of equivalent conductors, each one is representing the behavior of one group of conductors of the initial cable. Purpose. This work is focused on the development and implementation of simplified simulations to study electromagnetic couplings on multiconductor cable. Methods. This method requires a four step procedure which is summarized as follows. Two different cases, of one end grounded and two ends grounded configurations can be analyzed. Results. The results had shown that the model complexity and computation time are significantly reduced, without, however, reducing the accuracy of the calculations.Вступ. У цій статті метод еквівалентного кабельного джгута узагальнюється для прогнозування задач електромагнітного випромінювання кручених пар дротів. Новизна запропонованої роботи полягає в моделюванні багатожильного кабелю в спрощеному джгуті проводів, що складається зі зменшеної кількості еквівалентних провідників, кожен з яких репрезентує поведінку однієї групи провідників вихідного кабелю. Мета. Робота зосереджена на розробці та реалізації спрощеного моделювання для дослідження електромагнітних зв'язків у багатожильних кабелях. Методи. Цей метод вимагає чотириступінчастої процедури, яка коротко описана у статті. Можна проаналізувати два різні випадки: конфігурації із заземленням одного кінця та заземлення двох кінців. Результати. Результати показали, що складність моделі та тривалість обчислень значно знижуються, проте без зниження точності обчислень

Training Set Optimization in an Artificial Neural Network Constructed for High Bandwidth Interconnects Design

In this article, a novel training set optimization method in an artificial neural network (ANN) constructed for high bandwidth interconnects design is proposed based on rigorous probability analysis. In general, the accuracy of an ANN is enhanced by increasing training set size. However, generating large training sets is inevitably time-consuming and resource-demanding, and sometimes even impossible due to limited prototypes or measurement scenarios. Especially, when the number of channels in required design are huge such as graphics double data rate (GDDR) memory and high bandwidth memory (HBM). Therefore, optimizing the training set selection process is crucial to minimizing the training datasets for developing an efficient ANN. According to rigorous mathematical analysis of the uniformity of the training data by probability distribution function, optimization flow of the range selection is proposed to improve accuracy and efficiency. The optimal number of training data samples is further determined by studying the prediction error rates. The performance of the proposed method in terms of accuracy is validated by comparing the scattering parameters of arbitrarily chosen strip and microstrip type GDDR interconnects obtained from EM simulations with those predicted by ANNs using default and the proposed training-set selection methods

Electromagnetic Wave Theory and Applications

Contains table of contents for Section 3, reports on six research projects and a list of publications and conference papers.Joint Services Electronics Program Contract DAAL03-89-C-0001National Science Foundation Grant ECS 86-20029Schlumberger- Doll ResearchU.S. Army Research Office Contract DAAL03 88-K-0057U.S. Navy - Office of Naval Research Contract N00014-90-J-1002National Aeronautics and Space Administration Grant NAGW-1617U.S. Navy - Office of Naval Research Grant N00014-89-J-1107National Aeronautics and Space Administration Grant NAGW-1272National Aeronautics and Space Administration Agreement 958461U.S. Army - Corps of Engineers Contract DACA39-87-K-0022U.S. Air Force - Electronic Systems Division Contract F19628-88-K-0013U.S. Navy - Office of Naval Research Grant N00014-89-J-1019Digital Equipment CorporationIBM CorporationU.S. Department of Transportation Contract DTRS-57-88-C-00078Defence Advanced Research Projects Agency Contract MDA972-90-C-002

Efficient Computation of Cable Electromagnetic Compatibility Problems with Parametric Uncertainty

Cables are heavily used to transmit power and signals in various systems. However, due to the susceptibility of cable to conducted and radiated emissions, unintended response could be provoked in the cable, and therefore, degrade the system operation. This is referred to as the cable electromagnetic compatibility (EMC) problems. Deterministic simulations based on the nominal values of system variables are usually performed to predict the possible malfunction. However, the variables characterising the cable system are naturally random due to, e.g. manufacturing tolerance. As a result of the systemic uncertainty, the induced interference in the cable also becomes a random observable. Therefore, the statistical description of the cable interference is a more reasonable outcome for assessing the system risk. Accordingly, stochastic approaches are needed to produce the required statistical outcome. The conventional statistical approach to quantify the uncertainty of the system response is the Monte-Carlo (MC) method. However, the computational cost of the MC method could become overly expensive when dealing with a large number of random variables. Thus, the cable EMC problems in large platforms with multiple uncertainty sources cannot be efficiently solved using the MC method. Clearly, an efficient statistical approach needs to be sought to solve the challenging cable EMC problems in the real world. Very recently, the stochastic reduced order model (SROM) method was proposed in the field of mechanical engineering, and is known to have merits such as the non-intrusiveness feature and superior efficiency. Therefore, the potential of applying the SROM method for cable EMC problems is very promising, and thoroughly investigated in this thesis. This thesis presents a comprehensive study of the cable EMC problems. The contributions of this thesis are mainly twofold, comprising the investigation of cable interference caused by: (1) the conducted emission (mainly at intra-system level), and (2) the radiated emission when exposed to incident electromagnetic fields. In the case of parametric uncertainty, the statistical analysis of the induced interference is efficiently performed using the SROM method. Specifically, the first main contribution of this thesis is dedicated to the study of crosstalk phenomenon, i.e., the inference induced to a wire by nearby wires in the cable. A parametric study is performed to investigate the effect (i.e., by increasing or decreasing) of the cable configurational changes on the crosstalk variation. The result can also be used to suggest factors causing excessive crosstalk. Under the cable parametric uncertainty, the statistics of crosstalk is successfully predicted using the SROM method. The efficiency of the statistical analysis using the SROM method and its ease of implementation are clearly demonstrated, compared to the conventional MC method and another state-of-the-art statistical approach referred to as the stochastic collocation (SC) method. The sensitivity of crosstalk to different cable variables is efficiently quantified using the SROM method, and then ranked. With this ranking, the feasibility of reducing the complexity of stochastic EMC problems by ignoring weak parametric uncertainties is explored. The second significant contribution of this thesis is the efficient uncertainty quantification of the interference in the cable caused by random electromagnetic field illumination. The most complex scenario where the incident electromagnetic wave is assumed to be fully random is chosen for investigation. As a response to the random illumination, the statistics of the interference (i.e., the induced current) in the cable is efficiently obtained using the SROM method. The computational cost of the SROM method is shown to be significantly reduced by orders of magnitude, compared to those of the MC and SC methods. The result demonstrates the potential of the SROM method for the general problems of the cable system response to the random radiation field. Overall, the research presented in this thesis has successfully advanced the uncertainty propagation techniques for EMC problems, especially in the case of the cable interference. Based on the performance discussion, this thesis has also provided an in-depth knowledge about the merits and disadvantages of different stochastic methods, which helps EMC engineers perform the efficient statistical analysis for their specific problems

Mathematical and fuzzy modelling of high-speed interconnections in integrated circuits.

Microstrip line are the most popular interconnection type mainly due to its planar geometry. The mode of propagation is almost a transverse electromagnetic mode of wave propagation (TEM) and can be described by the Telegrapher's equations. These facts make mathematical and fuzzy modelling of microstrip lines possible.Two types of nonuniformly coupled microstrip lines, namely, nonuniformly spaced and strictly nonuniform, are presented in this study. A new model of capacitance matrix was developed for nonuniformly spaced coupled microstrip lines. The model obtained was then translated into a Mathematica program in order to be utilised in real systems. Furthermore, a new matrix; mutual capacitance ratio matrix, was deduced from the previous model. A few valuable properties were then established from this matrix. Novel concepts were introduced to approximate capacitance of strictly nonuniform coupled microstrip lines and Mathematica programs were coded to implement these methods. The study then continued with the development of new algorithms to calculate the time delay and characteristic impedance using capacitance matrices of both types of nonuniform lines. These algorithms finally became a generalised algorithm which could be used in any type of coupled microstrip lines, uniform and nonuniform. The time delay and characteristic impedance were later used as parameters to simulate crosstalk using SPICE. Analysis of geometrical and electrical parameters of microstrip lines was performed mathematically and simulations modelled using the Mathematica package. Experimental work was also carried out to investigate the characteristic of crosstalk. All information obtained from these analyses were then fed into the developed novel fuzzy model. The model was designed to minimise crosstalk and to optimise the geometrical and electrical parameters of coupled microstrip lines simultaneously. These models have the potential to become 'multi purpose on board designing tools' for a designer before the system is finally fabricated

Machine learning for the performance assessment of high-speed links

This paper investigates the application of support vector machine to the modeling of high-speed interconnects with largely varying and/or highly uncertain design parameters. The proposed method relies on a robust and well-established mathematical framework, yielding accurate surrogates of complex dynamical systems. An identification procedure based on the observation of a small set of system responses allows generating compact parametric relations, which can be used for design optimization and/or stochastic analysis. The feasibility and strength of the method are demonstrated based on a benchmark function and on the statistical assessment of a realistic printed circuit board interconnect, highlighting the main features and benefits of this technique over state-of-the-art solutions. Emphasis is given to the effects of the initial sample size and of input noise on the model estimation

Modeling for the Computer-Aided Design of Long Interconnects

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