4,793 research outputs found
Feature Papers of Forecasting 2021
No full textArticles in this book are Open Access and distributed under the Creative Commons Attribution (CC BY) license, which allows users to download, copy and build upon published articles, as long as the author and publisher are properly credited, which ensures maximum dissemination and a wider impact of our publications. The book as a whole is distributed by MDPI under the terms and conditions of the Creative Commons license CC BY-NC-ND
Optical and spectroscopic study of a supersonic flowing helium plasma: energy transport in the afterglow
No full textFlowing plasma jets are increasingly investigated and used for surface treatments, including biological matter, and as soft ionization sources for mass spectrometry. They have the characteristic capability to transport energy from the plasma excitation region to the flowing afterglow, and therefore to a distant application surface, in a controlled manner. The ability to transport and deposit energy into a specimen is related to the actual energy transport mechanism. In case of a flowing helium plasma, the energy in the flowing afterglow may be carried by metastable helium atoms and long-lived helium dimer ions. In this work a systematic investigation of the optical and spectroscopic characteristics of a supersonic flowing helium plasma in vacuum and its afterglow as function of the helium gas density is presented. The experimental data are compared with numerical modeling of the plasma excitation and helium dimer ion formation supported by a Computational Fluid Dynamic simulation of the helium jet. The results indicate that the plasma afterglow is effectively due to helium dimer ions recombination via a three-body reaction
A multi-discipline method to assess the human performance in manufacturing industry for safety and quality optimization
No full textNowadays the majority of organizations operating in manufacturing field recognize the importance of including the Human Factor contribution in the industrial process optimization (Hong et al. 2007). Technical measures and work organization procedures have been optimized in order to reduce the defects and waste generation but the Human Performance prediction still represents for Managers a difficult task to deal with.The prediction of the human performances of all workers involved in a production system would help Managers in better allocating the human resources. In order to reach this objective, a model to quantify the human capability of managing a complex task in a working context characterized by a set of physical, organizational and cognitive factors was designed.This paper presents the preliminary results of a three years industry/academia partnership project to assess the human performance in manufacturing plant. A multi-discipline approach involving both technical and individual factors was adopted
Fine-Grained Dynamic Resource Allocation for Big-Data Applications
No full textMany big-data applications are batch applications that exploit dedicated frameworks to perform massively parallel computations across clusters of machines. The time needed to process the entirety of the inputs represents the application's response time, which can be subject to deadlines. Spark, probably the most famous incarnation of these frameworks today, allocates resources to applications statically at the beginning of the execution and deviations are not managed: to meet the applications' deadlines, resources must be allocated carefully. This paper proposes an extension to Spark, called dynaSpark, that is able to allocate and redistribute resources to applications dynamically to meet deadlines and cope with the execution of unanticipated applications. This work is based on two key enablers: containers, to isolate Spark's parallel executors and allow for the dynamic and fast allocation of resources, and control-theory to govern resource allocation at runtime and obtain required precision and speed. Our evaluation shows that dynaSpark can (i) allocate resources efficiently to execute single applications with respect to set deadlines and (ii) reduce deadline violations (w.r.t. Spark) when executing multiple concurrent applications
Vehicle-to-Grid for peak shaving in a Medium Voltage Grid with PV plants
No full textThe global energy challenges impose important changes in electric energy production and transportation sectors, especially for developed countries. Today, the European road good transport sector and private mobility sector are crowded by different engine technologies which are evolving as real alternatives to internal combustion engine vehicles: in future years, an increase of electric vehicle penetration is expected. In this work, the effect of an electric vehicle fleet is simulated on a medium voltage grid, to analyze which are the effects of road transport sector electrification. A solution able to combine the batteries of electric vehicles and photovoltaic generators is proposed. Results of simulations on vehicle to grid application for peak shaving and considering profit criteria based on Day Ahead Market are discussed
Performance and Thermal Analysis of Organic Photovoltaic Modules in Outdoor Conditions
No full textOrganic photovoltaic (OPV) modules are an emerging, innovative and low-cost solution to convert sunlight into electricity. Their flexibility and semi-transparency make OPV modules a suitable solution even in applications that cannot be based on traditional photovoltaic (PV) technologies. However, high ageing rate, short lifetime and low efficiency have limited their diffusion. This paper presents two outdoor test campaigns designed to assess and to compare with traditional silicon-based PV technologies the power output of OPV modules operating in real environmental conditions. OPV modules, as well as silicon-based PV modules, were operated at their maximum power point for several days: data collected demonstrated that OPV power output is slightly enhanced by the cells temperature at low irradiance, while at high irradiance the temperature coefficient of power is close to zero. Unlike silicon-based PV technologies, quite constant maximum power point voltage regardless the OPV cells temperature justifies the latter result
Experimental status of 7Be production and destruction at astrophysical relevant energies
No full textThe production and destruction of 7Be plays a significant role in the Big Bang Nucleosynthesis as well as in the framework of the solar neutrino. The 3He(α, γ)7Be reaction cross sections has been measured several times in the last decades, but the precision achieved on reaction rate determinations at the relevant astrophysical energies is not yet satisfactory. The experimental status of this reaction will be critically reviewed, and the theoretical descriptions available will be discussed
Model-based PID autotuning enhanced by neural structural identification
No full textThis paper presents an autotuning method for industrial PID controllers in the 1-d.o.f. ISA form. The major feature of the method is that the model structure employed for the process is selected on-line based on a step response record, by means of a multilayer perceptron neural network. Thanks to the exclusive use of normalized I/O data, the network can be trained off-line with simulated data, therefore simplifying the method’s implementation. Once the model structure is selected and its parameters are identified, the IMC approach is used for synthesizing a regulator that is then approximated with a PID. Simulation and experimental results are reported to show the effectiveness of the proposed tuning method and its advantages with respect to IMC-based PID tuning with the model structure fixed a priori
An innovative tunable rule-based strategy for the predictive management of hybrid microgrids
No full textThis work proposes a methodology for the optimal training of rule-based management strategies, to be directly implemented in the industrial controller of hybrid off-grid microgrids. The parameters defining the control rules are optimally tuned resorting to different evolutionary algorithms, based on the expected operating conditions. The performance of the resulting management heuristics is compared with conventional approaches to optimal scheduling, including Mixed Integer Linear Programming (MILP) optimization, direct evolutionary scheduling optimization, and traditional non-trained heuristics. Results show how the trained heuristics achieve a performance very close to the global optimum found by the MILP solution, outperforming the other methods, and providing a single-layer commitment and dispatch algorithm which is easily deployable in the microgrid controller
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