Development of a simulation platform of all-electric aircraft on-board systems for energy management studies

This paper deals with the development of a simulation platform for the dynamic analysis of systems characterised by different physical domains. The research has been carried out in the context of the EC-funded Clean Sky Joint Technology Initiative (Green Regional Aircraft/All-Electric Aircraft domain). In particular, the objective of the research is focused on the on-board systems of new All-Electric Aircraft, where a crucial design point is related to the electrical energy management. In the “all-electric” concept, where pneumatic and hydraulic power systems are eliminated to improve aviation costs and environmental impact, the dynamics of electrical power absorptions is to be characterised and managed to avoid excessive peaks with respect to generators capabilities. The paper describes the architecture of a Matlab/Simulink simulation platform developed in order to design and validate of the electrical energy management logics, which lead up to 32% reduction of the maximum power request for the case study considered. Thanks to an approach based on a mixing of cosimulation and S-function compiling, the platform integrates models coming from different environments (AMESim, Dymola/Modelica), and developed by various partners/specialists

Wintertime thermal performance of green façades in a mediterranean climate

The increasing environmental issues have afforded opportunities for a widespread application of green systems in urban areas. Greening the building with green roofs and vertical green systems can be a design and retrofitting strategy to improve building energy performance in summer and in winter. Research efforts have been mainly concentrated on their energy saving function during warm periods. Green façades have a great application potential thanks to the space available in urban environment. The effect of green façades on building energy performance has been studied mainly for warm periods. In order to evaluate the effect during cold periods, an experiment was conducted in Bari, Italy, for two years. Pandorea jasminoides variegated and Rhyncospermum jasminoides were tested as evergreen climbing plants on walls; a third wall was used as control. The night-time temperature of the covered wall was higher than the uncovered wall temperature by up to 3.5°C, thanks to the presence of plants. The thermal barrier function performed by the vegetation layer was analysed. The influence of outdoor air temperature, relative humidity and wind velocity on the façades thermal effect during night-time was investigated. The experimental test demonstrated that both Pandorea jasminoides variegated and Rhyncospermum jasminoides are suitable for green façades in the Mediterranean climatic area during winter. The use of the green façades allowed increasing the thermal performance of the walls during night-time. They also reduced the surface temperature changes throughout the day

Reduction of Evapotranspiration in Microenvironment Conditions of Table Grape Vineyards Protected by Different Types of Plastic Covers

Saving water is a major challenge to increase environmental sustainability, particularly in semi-arid regions where most table grapes are produced. Water use is driven by atmospheric demand, which combines effects of solar radiation (prominent factor), wind, air temperature and humidity. Covering table grapes with transparent plastics is spread in many regions. Covers lower incoming solar radiation and wind speed, changing air temperature and humidity. This study assessed the effects of two plastic covers on reference evapotranspiration (ET0 ) in comparison to the open field. For two years, two vineyards (cv. Victoria) trained to overhead trellis systems (tendone) were covered with two transparent polyethylene sheets: an agrotextile fabric (C), and a commercial film (S). The sheet spectrophotometric properties were analyzed and the radiometric coefficients calculated. Micrometeorological data were recorded in the covered vineyards and in a nearby uncovered one. ET0 was calculated for June and July using the simplified Penman–Monteith equation. The coefficient of transmissivity to total photosynthetic radiation, a proxy of net radiation, was 73% for cover C and 83% for cover S. On average, ET0 decreased by 35% under cover C and 31% under cover S. Hence, in addition to providing protection from external agents, covers represent a valid tool for saving water in table grape viticulture; nevertheless, their radiometric properties should be considered and optimized to better achieve this goal

Implementing a GIS-Based Digital Atlas of Agricultural Plastics to Reduce Their Environmental Footprint: Part II, an Inductive Approach.

Plastic pollution, largely perceived by the public as a major risk factor that strongly impacts sea life and preservation, has an even higher negative impact on terrestrial ecosystems. Indeed, quantitative data about plastic contamination on agricultural soils are progressively emerging in alarming ways. One of the main contributors to this pollution involves the mismanagement of agricultural plastic waste (APW), i.e., the residues from plastic material used to improve the productivity of agricultural crops, such as greenhouse covers, mulching films, irrigation pipes, etc. Wrong management of agricultural plastics during and after their working lives may pollute the agricultural soil and aquifers by releasing macro-, micro-, and nanoplastics, which could also enter into the human food chain. In this study, we aimed to develop a methodology for the spatial quantification of agricultural plastics to achieve sustainable post-consumer management. Through an inductive approach, based on statistical data from the agricultural census of the administrative areas of the Italian provinces, an agricultural plastic coefficient (APC) was proposed, implemented, and spatialized in a GIS environment, to produce a database of APW for each type of crop. The proposed methodology can be exported to other countries. It represents valuable support that could realize, in integration with other tools, an atlas of agricultural plastics, which may be a starting point to plan strategies and actions targeted to the reduction of the plastic footprint of agriculture

Implementing a GIS-based Digital Atlas of Agricultural Plastics to Reduce Their Environmental Footprint. Part I: A Deductive Approach.

The agricultural sector has benefitted over the last century from several factors that have led to an exponential increase in its productive efficiency. The increasing use of new materials, such as plastics, has been one of the most important factors, as they have allowed for increased production in a simpler and more economical way. Various polymer types are used in different phases of the agricultural production cycle, but when their use is incorrectly managed, it can lead to different environmental impacts. In this study, an applied and simplified methodology to manage agricultural plastics monitoring and planning is proposed. The techniques used are based on quantification through the use of different datasets (orthophotos and satellite images) of the areas covered by plastics used for crop protection. The study area chosen is a part of the Ionian Coast of Southern Italy, which includes the most important municipalities of the Basilicata Region for fruit and vegetable production. The use of geographical techniques and observation methodologies, developed in an open‐source GIS environment, enabled accurate location of about 2000 hectares of agricultural land covered by plastics, as well as identification of the areas most susceptible to the accumulation of plastic waste. The techniques and the model implemented, due to its simplicity of use and reliability, can be applied by different local authorities in order to realize an Atlas of agricultural plastics, which would be applied for continuous monitoring, thereby enabling the upscaling of future social and ecological impact assessments, identification of new policy impacts, market searches, etc

Greenhouse localized heating powered by a polygeneration system

Energy consumption in greenhouse heating could reach up to 90% of the total energy requirement depending on the type of greenhouse, environmental control equipment and location of the greenhouse. The use of climate conditioning technologies that exploit renewable energy and the application of passive systems to improve the energy efficiency and the sustainability of the greenhouse sector are recommended. During winter 2020-2021, an experimental test was carried out at the University of Bari in a Mediterranean greenhouse heated by a polygeneration system, composed of a solar system and an air-water heat pump. Three localized heating systems were tested to transfer thermal energy close to plants of Roman lettuce. Heating pipes were placed inside the cultivation substrate in the underground pipe system and on the cultivation substrate in the laid pipe system. The third system consists of metal plates heated by steel tubes and placed in the aerial area of plants. A weather climatic station and a sensor system interfaced with a data logger for continuous data acquisition and storage were used. The plate system was the best for air temperature rising, as it allowed an increase of 3.6% compared to the set-up without any localised heating system. The underground pipe system was the best for the soil heating, as it achieved a temperature increase of 92%. Localized soil heating systems contributed significantly to an earlier harvest by almost 2 weeks

Nonacceptability criteria and closure properties for the class of languages accepted by binary systolic tree automata

AbstractIn this paper a contribution is given to the solution of the problem of finding an inductive characterization of the class of languages accepted by binary systolic tree automata, L(BSTA), in terms of the closure of a class of languages with respect to certain operations. It is shown that L(BSTA) is closed with respect to some new operations: selective concatenation, restricted concatenation and restricted iteration. The known nonclosure of L(BSTA) with respect to classical language operations, like concatenation and Kleene iteration is proved here by using a new nonacceptability criterion

BLUFF-BODIES VORTEX SHEDDING SUPRESSION BY DIRECT NUMERICAL SIMULATION

Vortex shedding is responsible for harmful vibrations on immersed structures and for increasing their drag coefficients. Thus vortex shedding suppression is highly interesting in order of decrease maintenance costs of standing structures and fuel costs on moving ones. Vortex shedding suppression is here achieved with the use of splitter plates by means of numerical simulations at a low Reynolds range, Re 100 and 160. For this purpose it has been used a high order finite difference method in association with a virtual boundary method, responsible for the obstacles representation. The use of this novel numerical method showed a great concordance with experimental results by means of low computational costs

Synthetic Data Pretraining for Hyperspectral Image Super-Resolution

Large-scale self-supervised pretraining of deep learning models is known to be critical in several fields, such as language processing, where its has led to significant breakthroughs. Indeed, it is often more impactful than architectural designs. However, the use of self-supervised pretraining lags behind in several domains, such as hyperspectral images, due to data scarcity. This paper addresses the challenge of data scarcity in the development of methods for spatial super-resolution of hyperspectral images (HSI-SR). We show that state-of-the-art HSI-SR methods are severely bottlenecked by the small paired datasets that are publicly available, also leading to unreliable assessment of the architectural merits of the models. We propose to capitalize on the abundance of high resolution (HR) RGB images to develop a self-supervised pretraining approach that significantly improves the quality of HSI-SR models. In particular, we leverage advances in spectral reconstruction methods to create a vast dataset with high spatial resolution and plausible spectra from RGB images, to be used for pretraining HSI-SR methods. Experimental results, conducted across multiple datasets, report large gains for state-of-the-art HSI-SR methods when pretrained according to the proposed procedure, and also highlight the unreliability of ranking methods when training on small datasets

Influence of Sward Height, Concentrate Supplementation and Season on Grazing Activity of Beef Cows

The influence of sward height, concentrate supplementation and season on daily pattern of forage consumption of lactating beef cows grazing cool season pastures was determined. Cows (n=24; BW=535±10.8 kg) were randomly assigned to eight plots maintained at sward heights (SH) of either 4-8 cm or 8-12 cm and fed three levels of concentrate supplement: none = 0 kg/day, low = 3.12 kg/day or high = 6.24 kg/day. Cows on lower SH had greater (P \u3c .08) forage dry matter intake and spent an additional 1.2 hours/day (P \u3c .01) grazing compared to the higher SH. Cows on lower SH consumed 7.7 kg/day of forage dry matter and grazed 9.4 hours/day whereas those on higher SH consumed 7.1 kg/day and grazed 8.2 hours/day. Cows on lower SH grazed 0.7 hours/day (P \u3c .06) and 0.4 hours/day (P \u3c .08) longer at 06:00-10:00 hour and 11:00-13:00 hour, respectively, compared to the higher SH. Grazing efficiency (kg of forage consumed/hour of grazing) decreased (P \u3c .01) as season progressed. Season influenced duration of grazing activity (P \u3c .01). Cows grazed 0.5 hours longer (P \u3c .01) at 06:00-10:00 hour late in summer (August) compared to spring (May) and mid summer (June/July). Cows grazed 0.3 hours longer (P \u3c .08) at 11:00-13:00 hour during spring compared to late summer