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Principles Of Optics Electromagnetic Theory Of Propagation Interference And Diffraction Of Light

The Geostationary Operational Environmental Satellite R-series (GOES-R) is the next block of four satellites to follow the existing GOES constellation currently operating over the Western Hemisphere. Advanced spacecraft and instrument technology will support expanded detection of environmental phenomena, resulting in more timely and accurate forecasts and warnings. Advancements over current GOES capabilities include a new capability for total lightning detection (cloud and cloud-to-ground flashes) from the Geostationary Lightning Mapper (GLM), and improved cloud and moisture imagery with the 16-channel Advanced Baseline Imager (ABI). The GLM will map total lightning activity continuously day and night with near-uniform storm-scale spatial resolution of 8 km with a product refresh rate of less than 20 s over the Americas and adjacent oceanic regions in the western hemisphere. This will aid in forecasting severe storms and tornado activity, and convective weather impacts on aviation safety and efficiency. In parallel with the instrument development, an Algorithm Working Group (AWG) Lightning Detection Science and Applications Team developed the Level 2 (stroke and flash) algorithms from the Level 1 lightning event (pixel level) data. Proxy data sets used to develop the GLM operational algorithms as well as cal/val performance monitoring tools were derived from the NASA Lightning Imaging Sensor (LIS) and Optical Transient Detector (OTD) instruments in low Earth orbit, and from ground-based lightning networks and intensive prelaunch field campaigns. The GLM will produce the same or similar lightning flash attributes provided by the LIS and OTD, and thus extend their combined climatology over the western hemisphere into the coming decades. Science and application development along with preoperational product demonstrations and evaluations at NWS forecast offices and NOAA testbeds will prepare the forecasters to use GLM as soon as possible after the planned launch and checkout of GOES-R in late 2015. New applications will use GLM alone, in combination with the ABI, or integrated (fused) with other available tools (weather radar and ground strike networks, nowcasting systems, mesoscale analysis, and numerical weather prediction models) in the hands of the forecaster responsible for issuing more timely and accurate forecasts and warnings.

The GOES-R Geostationary Lightning Mapper (GLM)

Description: A comprehensive reference on state–of–the–art EMC modeling. The problems of electromagnetic interference are as old as radio wave communication. Only recently, however, has progress in numerical computation permitted the creation of models that help explain the physical phenomena of EM interference and predict and mitigate their effects. These models also invite an approach to solving EMC problems that furthers an understanding of underlying principles. EMC Analysis Methods and Computational Models provides detailed descriptions of the formulation, development, analysis, and use of EMC models. Departing from the rules–of–thumb approach for predicting electromagnetic interference, this book covers every step in the development of computational models––from the electromagnetic topology of the system to the development of coupling, penetration, and propagation models that describe the behavior of energy within the system. Supported by numerous illustrations, it * Covers circuit theory, low–frequency coupling, discrete source radiation, transmission line propagation, EM field penetration through apertures, diffusion, and shielding. * Discusses the approximations necessary in model development and contrasts approximate models with more rigorous models. * Includes exercises that elaborate the theory behind the models and indicate practical applications. * Provides computer programs based on models developed in the text. For practicing engineers, researchers, and graduate students, this book broadens the base of knowledge about the principles of EMC and lays the foundation for future research in the field.

EMC Analysis Methods And Computational Models

The decoupling of modern printed circuit boards introduces a very complex task. Powerful stochastic optimizers are usually used to determine values and positions of decoupling capacitors on the board. The number of capacitors used has to be determined a priori by the user which brings problems with convergence of the optimization process or can lead to a waste of resources when the noises are to be attenuated to a certain level. In this paper, an approach based on the combination of time-domain contour integral method and optimization with variable number of dimensions is introduced. The optimizer works with models having variable dimensions and searches for the optimal one. The approach is tested on two example power circuit boards with various noise attenuation limits and constraints on capacitor positions and values.

PCB Decoupling Optimization With Variable Number of Capacitors

An iterative optimization for decoupling capacitor placement on a power delivery network (PDN) is presented based on Genetic Algorithm (GA) and Artificial Neural Network (ANN). The ANN is first trained by an appropriate set of results obtained by a commercial simulator. Once the ANN is ready, it is used within an iterative GA process to place a minimum number of decoupling capacitors for minimizing the differences between the input impedance at one or more location, and the required target impedance. The combined GA–ANN process is shown to effectively provide results consistent with those obtained by a longer optimization based on commercial simulators. With the new approach the accuracy of the results remains at the same level, but the computational time is reduced by at least 30 times. Two test cases have been considered for validating the proposed approach, with the second one also being compared by experimental measurements.

https://www.mdpi.com/2079-9292/9/8/1243/pdf

Effective PCB Decoupling Optimization by Combining an Iterative Genetic Algorithm and Machine Learning

FOPS : A new framework for the optimization with variable number of dimensions

The article proposes a multi-objective optimization method called Generalized Differential Evolution (GDE3) for a Variable Number of Dimensions (VND). The well-known generalized differential evolut...

Another evolution of generalized differential evolution: variable number of dimensions

The solution to the microwave imaging problem is often provided by systems that employ global optimization methods that search for material properties of the selected investigation domain. A novel method for the solution of the microwave imaging problem based on the optimization with a variable number of dimensions is introduced in this article. Shapes of scatterers with an arbitrary complexity can be coded in the form of decision space vectors with varying sizes. The variable number of dimensions formulation of the problem is compared to a conventional approach that uses a regular grid of sub-domains and the optimization algorithm then searches for material properties of individual sub-regions. The influence of the investigation domain parameters like the signal to noise ratio of the measured field, or scatterer's material properties on the stability of the method is discussed in the paper.

Microwave Imaging Using Optimization With Variable Number of Dimensions

The Antenna Toolbox For MATLAB (AToM), originally an in-house academic tool, has been transformed into a complete MATLAB toolbox, capable of modeling, discretizing and calculating arbitrarily shaped planar radiators while analysing the results. All tasks can be performed directly in MATLAB. The majority of the code allows its direct modification. AToM supports the latest features, used predominantly in the realm of electrically small antennas, namely modal decompositions, evaluation of fundamental bounds, and other techniques based on the source concept.

Martin Marek

Papers

PCB Decoupling Optimization With Variable Number of Capacitors

FOPS : A new framework for the optimization with variable number of dimensions

Another evolution of generalized differential evolution: variable number of dimensions

Microwave Imaging Using Optimization With Variable Number of Dimensions

AToM: a versatile MATLAB tool for antenna synthesis