Electric Sail-Based Displaced Orbits with a Refined Thrust Model

This paper analyzes the performance of an electric solar wind sail for generating and maintaining a heliocentric circular displaced orbit. Previous research on this subject was based on a simplified mathematical model of the spacecraft thrust. However, recent studies have proposed a more accurate algorithm for evaluating both the modulus and the direction of the propulsive thrust as a function of some important parameters related to the spacecraft attitude. Therefore, a reappraisal of the problem is motivated by the need to revise past results, taking into account new information available on the propulsion system. Within this context, this paper focuses on circular displaced orbits that are characterized in terms of orbital period, heliocentric distance and elevation angle. The attitude configuration and the value of the spacecraft characteristic acceleration required for orbital maintenance are calculated. An in-depth analysis of the linear stability of displaced orbits is given. It is shown that displaced orbits are unstable when the elevation angle exceeds about 20 deg

Optimization of electric vehicles charging station deployment by means of evolutionary algorithms

n/

An Approach to Physical Performance Analysis for Judo

Sport performance analysis is a technique that is becoming every year more important for athletes of every level. Many techniques have been developed to measure and analyse efficiently the performance of athletes in some sports, but in combat sports these techniques found in many times their limits, due to the high interaction between the two opponents during the competition. In this paper the problem will be framed. Moreover the physical performance measurement problem will be analysed and three different techniques to manage it will be presented. All the techniques have been used to analyse the performance of 22 high level Judo athletes

SNO Based Optimization for Shaped Beam Reflectarray Antennas

The design of a shaped beam reflectarray is a challenging issues. The problem can be hardly addressed by deterministic techniques or standard optimization due to the elevated number of design variables and its non-convex nature while can be much easily solved adopting Evolutionary Optimization Algorithms. In particular, in this paper a recently introduced evolutionary approach, named Social Network Optimization (SNO) has been applied to the design of a reduced size shaped beam reflectarray: the obtained numerical results are promising and prove the effectiveness of the adopted method

Role of Solar Irradiance Fluctuations on Optimal Solar Sail Trajectories

The aim of this work is to provide a systematic analysis for quantifying the impact of TSI fluctuations on minimum-time solar sail trajectories, in order to investigate the actual need of a control law able to counteract the environmental uncertainties

SNO-Based Design of Wide-Angle Beam-Scanning Reflectarrays

In this article, the design of a passive reflectarray with beam-scanning capabilities over a wide scan range is addressed. The proposed approach is based on the use of an efficient evolutionary algorithm, Social Network Optimization, and on the definition of a proper optimization environment that allows the simultaneous optimization of the antenna radiation pattern for different pointing directions, keeping under control the computational cost of the procedure. The effectiveness of the method is validated through the experimental characterization of a prototype, whose performance is also compared with that of a conventional bifocal configuration

An Efficient Artificial Intelligence Energy Management System for Urban Building Integrating Photovoltaic and Storage

The emerging leading role of green energy in our society pushes the investigation of new economic and technological solutions. Green energies and smart communities increase efficiency with the use of digital solutions for the benefits of inhabitants and companies. The paper focuses on the development of a methodology for the energy management, combining photovoltaics and storage systems, considering as the main case study a multi-story building characterized by a high density of households, used to generate data which allow feasibility foresights. The physical model of the algorithm is composed by two main elements: the photovoltaics modules and the battery energy storage system. In addition, to gain information about the real-time consumption a machine learning module is included in our approach to generate predictions about the near future demand. The benefits provided by the method are evaluated with an economic analysis, which computes the return of the investment using the real consumptions of a Boarding School, located in Turin (Italy). The case study analyzed in this article showed an increase in purchased energy at the minimum price from 25% to 91% and a 55% reduction in the electricity bill compared to most solutions on the market, with no additional costs and a stabilizing effect on the grid. Finally, the economic analysis shows that the proposed method is a profitable investment, with a breakeven point of thirteen years, due to the very simple implementation and the zero additional cost requested

Epidemiologia, prevenzione e trattamento delle malattie cardiovascolari: evidenze dal database della medicina generale

n/