The scaling of the single-pulse laser threshold fluence for dielectric breakdown with respect to pulse duration and material band gap energy was investigated in the subpicosecond pulse regime using oxide films ͑TiO 2 , Ta 2 O 5 , HfO 2 , Al 2 O 3 , and SiO 2 ͒. A phenomenological model attributes the pulse duration dependence to the interplay of multiphoton ionization, impact ionization, and subpicosecond electron decay out of the conduction band. The observed linear scaling of the breakdown fluence with band gap energy can be explained within the framework of this model by invoking the band gap dependence of the multiphoton absorption coefficient from Keldysh photoionization theory. The power exponent of the observed dependence of the breakdown threshold fluence F th on pulse duration p , F th ϰ p , is independent of the material and is attributed to photoionization seeded avalanche ionization.
Abstract:This chapter presents a fusion between discrete-e vent system s specifi cation (DEVS) and intelligent tools from soft computing. DEVS provides a robust and generic environment for modeling and simulation applications employing single work station, distributed, and real-time platforms. Soft computing is a consortium of tools for natural intelligence stemming from approx imate reasoning (fuzz y logic), learning (neural network or stochastic learning automaton), optimization (genetic algorithms and genetic programming), etc. The outcome of this fusion is what is called "Intelligent DEVS", called IDEVS here. IDEVS is an element of a virtual laboratory, called V-Lab® ., which is based on distributed multi-physics, multi-dynamic modeling techniques for multiple platforms . The chapter will introduce IDEVS and V-Lab®. and a theme example for a multi-agent simulation of a number of robot ic agents with a slew of dynamic models and multiple computer work station s. Chapter 11Key words: Soft computing, fuzzy logic, neural networks, genetic algorithms, virtual laboratory, discrete-event simulation, SLA, multi-agent systems, V-Lab®. , DEVS , IDEVS INTRODUCTIONThe past century has seen an evolution in the way man envisions robotics, from the earlier mechanical devices performing purely repetitive tasks to their more recent computer controlled and more intelligent and mobile counterparts --rovers. Even though several issues in robotics such as kinematics, dynamics and control of manipulator arms in a known environment seem to have reached a relative level of maturity, several new issues have arisen in the past several years which deal with increased need for autonomy and intelligence of rovers, increased uncertainty in rover environments, and increased complexity in coordinating rover-to-rover interaction and cooperation.Applications of the multi-agent architecture are many. Some of the earlier applications of multi-agent collaboration and coordination were in part assembly where two or more rovers worked to assemble two or more parts. Human-like robot hands were an example of several manipulator arms (fingers) cooperating in order to handle an ill-defined object. More recent applications have included self-healing minefields and formation flying of multiple air vehicles or satellites. For migrating birds, the formation flying provides for decreased overall drag, and hence, increased range. In case of air vehicles and micro satellites, we can also expect increased flexibility and robustness at lower cost [l]. In the case of self-healing landmines, mobile landmines autonomously reposition themselves to increase field's effectiveness after a breakage. In other applications, such as the exploration of the Martian landscape, rovers can be used to quickly map an unstructured environment, to move an object larger than any single rover could move or to cooperatively navigate in rough terrains similar to how humans use each other to jump over a wall. In general, such multi-agent based applications of rovers are seen most sui...
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