Geometric effects of sustainable auxetic structures integrating the particle swarm optimization and finite element method

The development of new materials based on industrial wastes has been the focus of much research for a sustainable world. The growing demand for tyres has been every year exacerbating environmental problems due to indiscriminate disposal in the nature, making a potentially harmful waste to public health. The incorporation of rubber particles from scrap tyres into polymeric composites has achieved high toughness and moderate mechanical properties. This work investigates the geometric effects (thickness, width and internal cell angle) of auxetic structures made of recycled rubber composites based on experimental and numerical data. The response surface models integrated with the swarm intelligence and finite element analysis were proposed in order to obtain a range of solutions that provides useful information to the user during the selection of geometric parameters for reentrant cells. The results revealed the cell thickness ranges from 39-40 mm and 5.98-6 mm, and the cell angle range from -0.01 to -0.06º maximize the ultimate strength. The same parameters were able to optimize the modulus of elasticity of rubber auxetic structures, excepting for the angle factor which must be set between -30º and 27.7º. The optimal Poisson's ratio was found when the cell angle ranged from -30º to -28.5º, cell width ranged from 5-5.6 mm and 2 mm in thickness

Large-scale unit commitment under uncertainty: an updated literature survey

The Unit Commitment problem in energy management aims at finding the optimal production schedule of a set of generation units, while meeting various system-wide constraints. It has always been a large-scale, non-convex, difficult problem, especially in view of the fact that, due to operational requirements, it has to be solved in an unreasonably small time for its size. Recently, growing renewable energy shares have strongly increased the level of uncertainty in the system, making the (ideal) Unit Commitment model a large-scale, non-convex and uncertain (stochastic, robust, chance-constrained) program. We provide a survey of the literature on methods for the Uncertain Unit Commitment problem, in all its variants. We start with a review of the main contributions on solution methods for the deterministic versions of the problem, focussing on those based on mathematical programming techniques that are more relevant for the uncertain versions of the problem. We then present and categorize the approaches to the latter, while providing entry points to the relevant literature on optimization under uncertainty. This is an updated version of the paper "Large-scale Unit Commitment under uncertainty: a literature survey" that appeared in 4OR 13(2), 115--171 (2015); this version has over 170 more citations, most of which appeared in the last three years, proving how fast the literature on uncertain Unit Commitment evolves, and therefore the interest in this subject