COLLGUN: a 3D FE Simulator for the Design of TWTs Electron Guns and Multistage Collectors

Coco, S.; Corsaro, Stefania; Laudani, Antonino; Pollicino, G.; Dionisio, Roberto; Martorana, R.

doi:10.1007/978-3-540-32862-9_25

Cited by 5 publications

(4 citation statements)

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“…Unfortunately the collector efficiency cannot be calculated analytically, due to the complexity of the electromagnetic problem under consideration. Specialized 3-D simulators are used by MDC designers to help them to analyze and test new and arbitrarily shaped geometries for high efficiency device (Coco et al, 2006), but the use of optimization techniques in the design process of these devices is rarely used, because of the high number of parameters and the high computational cost of efficiency evaluation (the fitness function) (Vaden et al, 2002;Ghosh and Carter, 2007;Petillo et al, 2007;Coco et al, 2012).…”

Section: Introductionmentioning

confidence: 99%

“…In this paper the authors present the application of a novel meta-heuristics technique called Metric-Topological-evolutionary-Optimization (MeTEO) , to the optimization of the electrodes' voltages of MDC, simulated by means of the code COLLGUN (Coco et al, 2006), a 3-D finite element (FE) simulator of collectors and electron guns. The FE approach has a great advantage of irregular meshes and the last version of the code COLLGUN is able to simulate complicated MDC geometry enough fast to be used in an optimization environment.…”

Section: Introductionmentioning

confidence: 99%

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Optimization of multistage depressed collectors using fem and parallel algorithm MeTEO

Coco

Laudani²,

Pulcini³

et al. 2013

COMPEL: The International Journal for Computation and Mathematics in Electrical and Electronic Engineering

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Purpose -This paper aims the application of a novel hybrid algorithm, called MeTEO, based on the combination of three heuristics inspired by artificial life to the optimization of electrodes voltages of multistage depressed collector. Design/methodology/approach -The flock-of-starlings optimization (FSO), the particle swarm optimization (PSO) and the bacterial chemotaxis algorithm (BCA) were adapted to implement a hybrid and parallel algorithm: the FSO has been powerfully employed for exploring the whole space of solutions, whereas the PSO þ BCA has been used to refine the FSO-found solutions, exploiting their better performances in local search. Findings -The optimization of the voltage of the electrodes of multistage depressed collector are efficiently handled with a moderate computational effort. Practical implication -The development of an efficient method for the solution of a complicated electromagnetic optimization problem, exploiting the different characteristic of different approaches based on evolutionary computation algorithm. Originality/value -The paper shows that the combination of stochastic methods having different exploration properties with appositely developed FE electromagnetic simulator allows us to produce effective solutions of multimodal electromagnetic optimization problems, with an acceptable computational cost.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Optimization of multistage depressed collectors using fem and parallel algorithm MeTEO

Coco

Laudani²,

Pulcini³

et al. 2013

COMPEL: The International Journal for Computation and Mathematics in Electrical and Electronic Engineering

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“…In fact a focusing magnetic field is usually present in the electron gun to obtain electron beam laminar and with a specific radius, in the interaction region to reduce the spread of the beam avoiding electrons' impinging on SWS, and in the collector to obtain a better distribution of the electrons on the electrodes and to reduce backstreaming current, due also to the secondary electron. Specialized 3D simulators, mostly based on finite element (FE) approach, are currently used by TWT designers to analyze and test new high efficiency devices, including the effect of self‐consistent magnetic field, the one generated from electron beam, and of the externally applied focusing magnetic field (Coco et al , 2006). Unfortunately, automatic optimization techniques in the design process of these devices are rarely used (Ghosh and Carter, 2007; Petillo et al , 2007; Vaden et al , 2002), because of the high computational cost of the simulation and of the high number of parameters from which the operation of this device depends: the geometry and the voltages of the electrodes and the applied focusing magnetic field, etc.…”

Section: Introductionmentioning

confidence: 99%

“…In this paper the authors present the application of a novel meta‐heuristics technique called metric‐topological‐evolutionary‐optimization (MeTEO) (Riganti Fulginei et al , 2011), to optimize the focusing magnetic structure of electron gun and multistage collectors of TWT, simulated by means of the 3D FE simulator COLLGUN (Coco et al , 2006). MeTEO is a hybrid algorithm composed by three different heuristics: flock of starlings optimization (FSO) (Riganti Fulginei and Salvini, 2009), particle swarm optimization (PSO), and bacterial chemotaxis algorithm (BCA).…”

Section: Introductionmentioning

confidence: 99%

TWT magnetic focusing structure optimization by parallel evolutionary algorithm

Coco

Laudani²,

Pollicino

et al. 2012

COMPEL - The International Journal for Computation and Mathematics in Electrical and Electronic Engineering

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"Purpose – The purpose of this paper is to present the application of a novel hybrid algorithm, called. MeTEO (Metric-Topological-Evolutionary-Optimization), based on the combination of three heuristics. inspired by artificial life to the solution of optimization problems of a real electronic vacuum device.. Design\/methodology\/approach – The Particle Swarm Optimization (PSO), the Flock-of-Starlings. Optimization (FSO) and the Bacterial Chemotaxis Algorithm (BCA) were adapted to implement a novel. meta-heuristic MeTEO the FSO has been powerfully employed for exploring the whole space of. solutions, whereas the PSO is used to explore local regions where FSO had found solutions, and BCA. to refine the solutions found by PSO, thanks its better performances in local search.. Findings – The optimization of the focusing magnetic field of a Travelling Wave Tubes (TWT). collector is presented in order to show the effectiveness of MeTEO, in combination with COLLGUN FE. simulator and equivalent source representation. The optimization of the focusing magnetic structure is. obtained by using a maximum of 100 steps for each heuristic.. Practical implications – The paper describes the development of a novel efficient parallel method. for the solution of electromagnetic device optimization problems.. Originality\/value – The paper shows the capabilities of a novel combination of optimization methods. inspired by “artificial life” which allows us to achieve effective solutions of multimodal optimization. problems, typical of the electromagnetic device optimization, with an acceptable computational cost,. thanks also to its natural parallel implementation.

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