Design, manufacturing, evaluation, and performance of a 3D-printed, custom-made nozzle for laser wakefield acceleration experiments.

Laser WakeField Acceleration (LWFA) is extensively used as a high-energy electron source, with electrons achieving energies up to the GeV level. The produced electron beam characteristics depend strongly on the gas density profile. When the gaseous target is a gas jet, the gas density profile is affected by parameters, such as the nozzle geometry, the gas used, and the backing pressure applied to the gas valve.

The influence of the solid to plasma phase transition on the generation of plasma instabilities.

The study of plasma instabilities is a research topic with fundamental importance since for the majority of plasma applications they are unwanted and there is always the need for their suppression. The initiating physical processes that seed the generation of plasma instabilities are not well understood in all plasma geometries and initial states of matter. For most plasma instability studies, using linear or even nonlinear magnetohydrodynamics (MHD) theory, the most crucial step is to correctly choose the initial perturbations imposed either by a predefined perturbation, usually sinusoidal, or by randomly seed perturbations as initial conditions.

Computational benefits using artificial intelligent methodologies for the solution of an environmental design problem: saltwater intrusion.

Artificial Neural Networks (ANNs) comprise a powerful tool to approximate the complicated behavior and response of physical systems allowing considerable reduction in computation time during time-consuming optimization runs. In this work, a Radial Basis Function Artificial Neural Network (RBFN) is combined with a Differential Evolution (DE) algorithm to solve a water resources management problem, using an optimization procedure. The objective of the optimization scheme is to cover the daily water demand on the coastal aquifer east of the city of Heraklion, Crete, without reducing the subsurface water quality due to seawater intrusion.

Evolutionary algorithm based offline/online path planner for UAV navigation.

An evolutionary algorithm based framework, a combination of modified breeder genetic algorithms incorporating characteristics of classic genetic algorithms, is utilized to design an offline/online path planner for unmanned aerial vehicles (UAVs) autonomous navigation. The path planner calculates a curved path line with desired characteristics in a three-dimensional (3-D) rough terrain environment, represented using B-spline curves, with the coordinates of its control points being the evolutionary algorithm artificial chromosome genes. Given a 3-D rough environment and assuming flight envelope restrictions, two problems are solved: i) UAV navigation using an offline planner in a known environment, and, ii) UAV navigation using an online planner in a completely unknown environment.