Scalable methodology for the photovoltaic solar energy potential assessment based on available roof surface area: Application to Piedmont Region (Italy)

During the last few years the photovoltaic energy market has seen an outstanding growth. According to the new directive on renewable energies of the European Commission (2009/28/EC), the European Union should reach a 20% share of the total energy consumption from renewable sources by 2020. The national overall targets impose for Italy a 17% renewable share: in case of failure the gap would be filled by importation of renewable energy from non-UE countries. The ambitious national targets and thus the continuously increasing interest on renewable fuels, require simple but reliable methods for the energy potential assessment over large-scale territories. Considering roof-top integrated PV systems, the assessment of the PV energy potential passes through the evaluation of the roof surface area available for installations. In the present paper a methodology for estimating the PV solar energy potential is presented, together with its application to Piedmont Region (North-Western Italy). The roof area suitable for solar applications, is calculated through the analysis of available GIS data. The solar radiation maps are taken from the database of the Joint Research Centre of the European Commission. Different solar energy exploitation scenarios are proposed with the relative perspective results and confidence interval. Further developments and applications of the presented methodology are finally discussed.     

Property specification patterns at work: verification and inconsistency explanation

Innovations in Systems and Software Engineering - Property specification patterns (PSPs) have been proposed to ease the formalization of requirements, yet enable automated verification thereof. In...     

Designing a personal informatics system for users without experience in self-tracking: a case study

Thanks to the advancements in ubiquitous and wearable technologies, Personal Informatics (PI) systems can now reach a larger audience of users. However, it is not still clear whether this kind of tool can fit the needs of their daily lives. Our research aims at identifying specific barriers that may prevent the widespread adoption of PI and finding solutions to overcome them. We requested users without competence in self-tracking to use different PI instruments during their daily practices, identifying five user requirements by which to design novel PI tools. On such requirements, we developed a new system that can stimulate the use of these technologies, by enhancing the perceived benefits of collecting personal data. Then, we explored how naïve and experienced users differently explore their personal data in our system through a user trial. Results showed that the system was successful at helping individuals manage and interpret their own data, validated the usefulness of the requirements found and inspired three further design opportunities that could orient the design of future PI systems.     

Sensitivity Analysis and Model Validation of a 2-DoF Mini Spherical Robot

This paper is focused on the development and validation of an error kinematic model of a mini spherical robot, aimed at its kinematic calibration. The robot is actually a spatial five-bar linkage, provided with two rotational degrees of freedom. A non-overconstrained kinematics is assumed for the robot in order to provide a simple mathematical model and allow a sensitivity analysis of all the involved geometric parameters. A simplified version of the model is proposed. It differs only for the degree of approximation. A comparison between full and reduced models is presented by means of numerical simulations, analyzing their behavior in a significant region of the robot workspace. In order to validate both of them a robot calibration is carried out on a physical prototype of the robot using a vision system, namely a fixed camera in a eye-to-hand configuration. An iterative algorithm aimed at the experimental identification of the geometric data of the robot is used. Some experimental results show the effectiveness of the study.     

Monte Carlo uncertainty quantification of the effective delayed neutron fraction

The applicability of Monte Carlo techniques, namely the Monte Carlo sensitivity method and the random-sampling method, for uncertainty quantification of the effective delayed neutron fraction β_eff is investigated using the continuous-energy Monte Carlo transport code, MCNP, from the perspective of statistical convergence issues. This study focuses on the nuclear data as one of the major sources of β_eff uncertainty. For validation of the calculated β_eff, a critical configuration of the VENUS-F zero-power reactor was used. It is demonstrated that Chiba's modified k-ratio method is superior to Bretscher's prompt k-ratio method in terms of reducing the statistical uncertainty in calculating not only β_eff but also its sensitivities and the uncertainty due to nuclear data. From this result and a comparison of uncertainties obtained by the Monte Carlo sensitivity method and the random-sampling method, it is shown that the Monte Carlo sensitivity method using Chiba's modified k-ratio method is the most practical for uncertainty quantification of β_eff. Finally, total β_eff uncertainty due to nuclear data for the VENUS-F critical configuration is determined to be approximately 2.7% with JENDL-4.0u, which is dominated by the delayed neutron yield of ²³⁵U.     

Supercritical CO2 extraction of grape seeds oil: scale-up and economic analysis

This work presents a scale-up and feasibility study for the establishment of supercritical CO₂ extraction plants to produce grape seeds oil. The scale-up factors are determined using experimental and modelling results based on seeds from six grape cultivars over 2 harvest years. The purchased cost of the production plant is estimated using ‘the six-tenth rule’ from the cost of a pilot scale unit. The results indicate that, at the current minimum retail selling price of extra virgin grape seeds oil, the proposed project is technically viable and economically feasible with a breakeven point of US$ 7.46 per kg-oil and rate of return on investment of 28%.     

Experimental validation of a geographical information systems-based procedure for predicting pesticide exposure in surface water

A GIS-based procedure for predicting pesticide exposure in surface waters has been applied on a pilot river basin characterized by intensive agricultural activity. The predictive approach has been validated through experimental monitoring, performed by collecting manual and automatic water samples during the productive season. Five active ingredients (terbuthylazine, metolachlor, alachlor, linuron, fenitrothion) were selected for analysis to validate the predictive approach. Comparison between predicted and experimental values showed good agreement for terbuthylazine and metolachlor (used in large volumes within the basin), demonstrating the reliability of the approach. However, some anomalous results were obtained for some of the other chemicals, which serve to highlight the difficulties in getting reliable input data, in particular on application patterns (rate and time). Furthermore, the value of mapping pesticide exposure on the medium-large scale is described, and the limitations of the reported predictive approach are discussed.