Epipolar geometry estimation based on evolutionary agents

This paper presents a novel approach based on the use of evolutionary agents for epipolar geometry estimation. In contrast to conventional nonlinear optimization methods, the proposed technique employs each agent to denote a minimal subset to compute the fundamental matrix, and considers the data set of correspondences as a 1D cellular environment, in which the agents inhabit and evolve. The agents execute some evolutionary behavior, and evolve autonomously in a vast solution space to reach the optimal (or near optima) result. Then three different techniques are proposed in order to improve the searching ability and computational efficiency of the original agents. Subset template enables agents to collaborate more efficiently with each other, and inherit accurate information from the whole agent set. Competitive evolutionary agent (CEA) and finite multiple evolutionary agent (FMEA) apply a better evolutionary strategy or decision rule, and focus on different aspects of the evolutionary process. Experimental results with both synthetic data and real images show that the proposed agent-based approaches perform better than other typical methods in terms of accuracy and speed, and are more robust to noise and outliers.

Laser-Driven Proton Beams: Acceleration Mechanism, Beam Optimization, and Radiographic Applications

This paper reviews recent experimental activity in the area of optimization, control, and application of laser accelerated proton beams, carried out at the Rutherford Appleton Laboratory and the Laboratoire pour l’Utilisation des Lasers Intenses 100 TW facility in France. In particular, experiments have investigated the role of the scale length at the rear of the plasma in reducing target-normal-sheath-acceleration acceleration efficiency. Results match with recent theoretical predictions and provide information in view of the feasibility of proton fast-ignition applications. Experiments aiming to control the divergence of the proton beams have investigated the use of a laser-triggered microlens, which employs laser-driven transient electric fields in cylindrical geometry, enabling to focus the emitted
protons and select monochromatic beam lets out of the broad spectrum beam. This approach could be advantageous in view
of a variety of applications. The use of laser-driven protons as a particle probe for transient field detection has been developed and
applied to a number of experimental conditions. Recent work in this area has focused on the detection of large-scale self-generated magnetic fields in laser-produced plasmas and the investigation of fields associated to the propagation of relativistic electron both on the surface and in the bulk of targets irradiated by high-power laser pulses.

Generation and optimization of electron currents along the walls of a conical target for fast ignition

The interaction of an ultraintense laser pulse with a conical target is studied by means of numerical particle-in-cell simulations in the context of fast ignition. The divergence of the fast electron beam generated at the tip of the cone has been shown to be a crucial parameter for the efficient coupling of the ignition laser pulse to the precompressed fusion pellet. In this paper, we demonstrate that a focused hot electron beam is produced at the cone tip, provided that electron currents flowing along the surfaces of the cone sidewalls are efficiently generated. The influence of various interaction parameters over the formation of these wall currents is investigated. It is found that the strength of the electron flows is enhanced for high laser intensities, low density targets, and steep density gradients inside the cone. The hot electron energy distribution obeys a power law for energies of up to a few MeV, with the addition of a high-energy Maxwellian tail.

Shape optimization of interior cutouts in composite panels

This paper presents validated results of the optimization of cutouts in laminated carbon-fibre composite panels by adapting a recently developed optimization procedure known as Evolutionary Structural Optimization (ESO). An initial small cutout was introduced into each finite element model and elements were removed from around this cutout based on a predefined rejection criterion. In the examples presented, the limiting ply within each plate element around the cutout was determined based on the Tsai-Hill failure index. Plates with values below the product of the average Tsai-Hill number and a rejection ratio (RR) were subsequently removed. This process was iterated until a steady state was reached and the RR was then incremented by an evolutionary rate (ER). The above steps were repeated until a cutout of a desired area was achieved.