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Abstract In the present work the problem of the on-line monitoring of the reactivity in a source-free nuclear reactor is considered. The method is based on the classic point kinetic model of reactor physics. A relationship between the instantaneous value of the system stable period and the values of the neutron flux amplitude (or the power), of its derivative and of the integral convolution term determining the instantaneous value of the effective delayed neutron concentration is derived. The reactivity can then be evaluated through the application of the inhour equation, assuming the effective delayed neutron fraction and prompt generation time are known from independent measurements. Since the power related quantities can be assumed to be experimental observables at each instant, the reactivity can be easily reconstructed. The method is tested at first through the interpretation of power histories simulated by the solution of the point kinetic equations; the effect of the time interval between power detections on the accuracy is studied, proving the excellent performance of the procedure. The work includes also a study on the sensitivity of the reactivity forecast to the uncertainty on the values of the effective delayed neutron fraction and prompt generation time. The spatial effects are investigated by applying the method to the interpretation of flux evolution histories generated by a numerical code solving the space–time dependent neutron kinetic equations in the diffusion model. Also in this case the method proves to be quite effective in providing good estimates of the system reactivity, except at very short times after the introduction of a perturbation inducing a spatial transient. At last, the effect of the experimental noise is investigated, proving that the consequences in the accuracy of the reactivity prediction can be mitigated by using an adequate differentiation algorithm.

AbstractThe use of thermal insulating plasters represents an effective solution in energy retrofit of existing buildings. Thermal properties are usually improved through the addition on the plaster formulation of Light Weight Aggregates, as expanded polystyrene and perlite. The drawback of these thermal plasters is the higher environmental impact, especially when added to natural binders, as natural hydraulic lime.Within a research activity a process of optimization was followed in order to get the most effective blend, applying iteratively the LCA methodology, measuring the thermal conductivity and testing the environmental impact in terms of Volatile Organic Compounds and formaldehyde emission rates.

During water electrolysis, adding an electrocatalyst for the hydrogen evolution reaction (HER) is necessary to reduce the activation barrier and thus enhance the reaction rate. Metal chalcogenide-based 2D nanomaterials have been studied as an alternative to noble metal electrocatalysts because of their interesting electrocatalytic properties and low costs of production. However, the difficulty in improving the catalytic efficiency and industrializing the synthetic methods have become a problem in the potential application of these species in electrocatalysis. Liquid-phase exfoliation (LPE) is a low-cost and scalable technique for lab- and industrial-scale synthesis of 2D-material colloidal inks. In this work, we present, to the best of our knowledge, for the first time a systematic study on the surfactant-assisted LPE of bulk Bi2S3 crystalline powder to produce nanosheets (NSs). Different dispersing agents and LPE conditions have been tested in order to obtain colloidal low-dimensional Bi2S3 NSs in H2O at optimized concentrations. Eventually, colloidally stable layered nano-sized Bi2S3 suspensions can be produced with yields of up to ~12.5%. The thus obtained low-dimensional Bi2S3 is proven to be more active for HER than the bulk starting material, showing an overpotential of only 235 mV and an optimized Tafel slope of 125 mV/dec. Our results provide a facile top-down method to produce nano-sized Bi2S3 through a green approach and demonstrate that this material can have a good potential as electrocatalyst for HER.

Energy Certificates of Buildings (ECB) provide interesting information on the standard energy performance, thermo-physical and geometrical related properties of existing buildings. The analysis of such data collection is challenging due to data volume and heterogeneity of attributes. This paper presents EPICA a data mining framework to automatically explore a collection of ECB to extract interesting knowledge items. To this aim, EPICA first reduces the data dimensionality through the Principal Component Analysis, then a clustering algorithm is exploited to discover groups of ECB with similar features. Each group is then locally characterized by a set of relevant generalized association rules able to summarize interesting relations among variables influencing energy performance of buildings at different coarse granularities. Experimental results, obtained on real data collected from an energy certification dataset related to Piedmont Region, in North Western of Italy, shows the effectiveness of EPICA in extracting a manageable set of human-readable knowledge items characterizing the groups of buildings with different energy performance levels.

The recent dispositions related to the energy performance of buildings, launched by the European Directives 2002/91/EC and 2010/31/EU, turned attention to the Energy Performance Certificate (EPC). The aim of this study is to investigate the economic effects of the recent Italian statutory provisions related to energy performance of buildings on listing behaviour. With this aim an hedonic regression analysis is performed, in order to measure the impact of EPC level on listing prices. The study, based on a set of more than 500 housing property asset collected in 2012 from real estate advertisements websites, is focused on the Turin real estate market as a case study. Furthermore this paper contributes to the early limited literature on implication of the impact of EPC level on Italian housing market, representing one of the first systematic evidence about the energy certifications in the housing listing prices. Aestimum, Aestimum 65 (2014)

In contemporary urban logistics, drones will become a preferred transportation mode for last-mile deliveries, as they have shown commercial potential and triple-bottom-line performance. Drones, in fact, address many challenges related to congestion and emissions and can streamline the last leg of the supply chain, while maintaining economic performance. Despite the common conviction that drones will reshape the future of deliveries, numerous hurdles prevent practical implementation of this futuristic vision. The sharing economy, referred to as a collaborative business model that foster sharing, exchanging and renting resources, could lead to operational improvements and enhance the cost control ability and the flexibility of companies using drones. For instance, the Amazon patent for drone beehives, which are fulfilment centers where drones can be restocked before flying out again for another delivery, could be established as a shared delivery systems where different freight carriers jointly deliver goods to customers. Only a few studies have addressed the problem of operating such facilities providing services to retail companies. In this paper, we formulate the problem as a deterministic location-routing model and derive its robust counterpart under the travel time uncertainty. To tackle the computational complexity of the model caused by the non-linear energy consumption rates in drone battery, we propose a tailored matheuristic combining variable neighborhood descent with a cut generation approach. The computational experiments show the efficiency of the solution approach especially compared to the Gurobi solver.

AbstractSwitchable windows are glazing technologies that exhibit dynamic optical properties and may thus be used to improve the energy performance of buildings. A window system based on a thermotropic glass pane was tested both in the laboratory and by means of an outdoor test cell facility.In this paper the full optical and thermal characterization of this glazing technology is presented. Experiments and data analysis led to the characterization of the behaviour of the thermotropic glazing both when this technology is used alone (single glass pane) and when it is integrated in a multilayer fenestration (a triple glazed unit).