Search results for "Annealing"

Variation of lattice constant and cluster formation in GaAsBi

2013

We investigate the structural properties of GaAsBi layers grown by molecular beam epitaxy on GaAs at substrate temperatures between 220–315 C. Irrespective of the growth temperature, the structures exhibited similar Bi compositions, and good overall crystal quality as deduced from X-Ray diffraction measurements. After thermal annealing at temperatures as low as 500 C, the GaAsBi layers grown at the lowest temperatures exhibited a significant reduction of the lattice constant. The lattice variation was significantly larger for Bi-containing samples than for Bi-free low-temperature GaAs samples grown as a reference. Rutherford backscattering spectrometry gave no evidence of Bi diffusing out o…

Atomic layer deposition of LixTiyOz thin films

2013

Atomic layer deposition (ALD) was employed to deposit ternary films of LixTiyOz. The film growth at a deposition temperature of 225 °C was studied using both titanium tetra-isoropoxide (Ti(OiPr)4) and titanium tetrachloride (TiCl4) as titanium precursors. Lithium tert-butoxide (LiOtBu) was applied as the lithium source and water was used as the oxygen source for all metal precursors. The type of titanium precursor chosen strongly affected film growth: with TiCl4 the resulting LixTiyOz films were highly air-sensitive and the lithium concentration was low, whereas with Ti(OiPr)4 the films were relatively stable in air and with a lithium content which was easily controlled over a wide range. F…

Effect of annealing below the glass transition on the loss peak of glassy polycarbonate

1980

A fast heuristic for solving the D1EC coloring problem

2010

In this paper we propose an efficient heuristic for solving the Distance-1 Edge Coloring problem (D1EC) for the on-the-fly assignment of orthogonal wireless channels in wireless as soon as a topology change occurs. The coloring algorithm exploits the simulated annealing paradigm, i.e., a generalization of Monte Carlo methods for solving combinatorial problems. We show that the simulated annealing-based coloring converges fast to a sub optimal coloring scheme even for the case of dynamic channel allocation. However, a stateful implementation of the D1EC scheme is needed in order to speed-up the network coloring upon topology changes. In fact, a stateful D1EC reduces the algorithm’s convergen…

Time scales of adaptive behavior and motor learning in the presence of stochastic perturbations.

2009

In this paper, the major assumptions of influential approaches to the structure of variability in practice conditions are discussed from the perspective of a generalized evolving attractor landscape model of motor learning. The efficacy of the practice condition effects is considered in relation to the theoretical influence of stochastic perturbations in models of gradient descent learning of multiple dimension landscapes. A model for motor learning is presented combining simulated annealing and stochastic resonance phenomena against the background of different time scales for adaptation and learning processes. The practical consequences of the model's assumptions for the structure of pract…

Stochastic reconstruction of sandstones

2000

A simulated annealing algorithm is employed to generate a stochastic model for a Berea and a Fontainebleau sandstone with prescribed two-point probability function, lineal path function, and ``pore size'' distribution function, respectively. We find that the temperature decrease of the annealing has to be rather quick to yield isotropic and percolating configurations. A comparison of simple morphological quantities indicates good agreement between the reconstructions and the original sandstones. Also, the mean survival time of a random walker in the pore space is reproduced with good accuracy. However, a more detailed investigation by means of local porosity theory shows that there may be s…

A novel heuristics-based energy management system for a multi-carrier hub enriched with solid hydrogen storage

2014

In this paper, an efficient optimization algorithm for the energy management of a grid-connected energy hub plant is proposed. The Simulated Annealing algorithm is adopted for the solution of the energy management problem aiming at the profit maximization for the owner of the energy hub plant. The use of a heuristic algorithm was required by the non-linearity of the efficiencies of each component in the energy transformation stages. The proposed heuristics is applied to a large energy hub, corresponding to the simulation of the test-bed that is being designed and developed inside the ongoing INGRID European research project.

Implementing some Evolutionary Computing Methods for Determining the Optimal Parameters in the Turning Process

2015

In this paper, we comparatively present two heuristics search methods – Simulated Annealing and Weighted Sum Genetic Algorithm, in order to find optimal cutting parameters in turning operation. We consider five different constraints aiming to achieve minimum total cost of machining. We developed a customizable software application in Microsoft Visual Studio with C# source code, flexible and extensible that implements the optimization methods. The experiments are based on real data gathered from S.C. “Compa” S.A Sibiu, a company that manufactures automotive components and targets improving of product quality and reducing cost and production time. The obtained results show that, although the …

Biased Modern Heuristics for the OCST Problem

2011

Biasing modern heuristics is an appropriate possibility in designing problem-specific and high-quality modern heuristics. If we have knowledge about a problem we can bias the design elements of modern heuristics, namely the representation and search operator, fitness function, the initial solution, or even the search strategy. This chapter presents a case study on how the performance of modern heuristics can be increased by biasing the design elements towards high-quality solutions. Results show that problem-specific and biased modern heuristics outperform standard variants and even for large problem instances high-quality solutions can be found.

Hydropower Optimization Using Split-Window, Meta-Heuristic and Genetic Algorithms

2019

In this paper, we try to find the most efficient optimization algorithm that can be used to resolve the hydropower optimization problem. We propose a novel optimization technique is called the Split-window method. The method is relatively simple and reduces the complexity of the optimization problem by split-ting the planning horizon (and datasets) into equal windows and assigning the same values to policies(actions) within each part. After splitting, a meta-heuristic technique is used to optimize the actions, and the dataset is split again until a split contains only one instance (timestep). The unique values to be optimized during each iteration is equal to the number of splits which make…