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<p>In the framework of H2020, the European Commission recently funded the project ReSHEALience (www.uhdc.eu). The main idea behind the project is that the long-term behaviour of structures under extremely aggressive exposure conditions can highly benefit from the use of high performance materials, in the framework of durability-based design approaches. The project consortium, coordinated by Politecnico di Milano, features 14 partners from 8 different countries, including 6 academic/research institutions and 8 industrial partners, covering the whole value chain from producers of concrete constituents to construction companies to stake-holders and end-users. The main goals of the project are the development (a) of an Ultra High Durability Concrete (UHDC) and (b) a Durability Assessment-based Design (DAD) methodology to improve structure durability and predict long-term performance under Extremely Aggressive Exposures (EAE). The project will tailor the composition of UHDC, by upgrading the UHPC/UHPFRC concept through the incorporation of tailored nanoscale constituents.</p>

This paper provides an overview of objectives, structure and first results of the DEMOYS project, financially supported by the European Commission in the frame of the 7th FP Energy. The project started on May 1, 2010 and brings together fifteen Partners, including three Universities, five Research Organizations and seven Industries. The objective of DEMOYS is the development of thin mixed conducting membranes for O-2 and H-2 separation by using a new deposition technique "Plasma Spraying - Thin Film" (PS-TF) in combination with nano-porous, highly catalytic layers. (C) 2013 The Authors. Published by Elsevier Ltd. Open access under CC BY-NC-ND license. Selection and/or peer-review under responsibility of GHGT DEMOYS receives funding from the European Community's Seventh Framework Programme, FP7/2007-2013, under grant agreement no 241309.

Monitoring of sensor operation is important for detecting anomalies and reconstructing the correct values of the signals measured. This can be done, for example, with the aid of auto-associative regression models. However, in practical applications, difficulties arise because of the need for handling large numbers of signals. To overcome these difficulties, ensembles of reconstruction models can be used. Each model in the ensemble handles a small group of signals and the outcomes of all models are eventually combined to provide the final outcome. In this work, three different methods for aggregating the model outcomes are investigated and a novel procedure is proposed for obtaining robust ensemble-aggregated outputs. Two applications are considered concerning the reconstruction of 920 simulated signals of the Swedish Forsmark-3 Boiling Water Reactor (BWR) and 215 signals measured at the Finnish Pressurised Water Reactor (PWR) situated in Loviisa.

Abstract Disposal facilities are designed to provide long-term isolation of the wastes from the human environment by means of a system of barriers, both engineered and natural. In this regard, it is required that the containment function of the multi-barrier system be evaluated by a quantitative risk analysis procedure, also called performance assessment. This entails the implementation of a Probabilistic Safety Assessment model for representing the stochastic failure behavior of the repository barriers, estimating the release rates of radionuclides into the groundwater stream and the doses from subsequent ingestion of drinking water. To this aim, a Monte Carlo simulation scheme is provided within a reliability modelling approach for the safety performance analysis of a repository, accounting also for barrier degradation processes. An application to a case study of the literature is presented to validate the approach and demonstrate its simplicity and flexibility.

This paper proposes a novel framework for the analysis of integrated energy systems (IESs) exposed to both stochastic failures and “shock” climate-induced failures, such as those characterizing NaTech accidental scenarios. With such a framework, standard centralized systems (CS), IES with distributed generation (IES-DG) and IES with bidirectional energy conversion (IES+P2G) enabled by power-to-gas (P2G) facilities can be analyzed. The framework embeds the model of each single production plant in an integrated power-flow model and then couples it with a stochastic failures model and a climate-induced failure model, which simulates the occurrence of extreme weather events (e.g., flooding) driven by climate change. To illustrate how to operationalize the analysis in practice, a case study of a realistic IES has been considered that comprises two combined cycle gas turbine plants (CCGT), a nuclear power plant (NPP), two wind farms (WF), a solar photovoltaicS (PV) field and a power-to-gas station (P2G). Results suggest that the IESs are resilient to climate-induced failures.

In an integrated biorefinery concept, biological hydrogen and methane production from lignocellulosic substrates appears to be one of the most promising alternatives to produce energy from renewable sources. However, lignocellulosic substrates present compositional and structural features that can limit their conversion into biohydrogen and methane. In this study, biohydrogen and methane potentials of 20 lignocellulosic residues were evaluated. Compositional (lignin, cellulose, hemicelluloses, total uronic acids, proteins, and soluble sugars) as well as structural features (crystallinity) were determined for each substrate. Two predictive partial least square (PLS) models were built to determine which compositional and structural parameters affected biohydrogen or methane production from lignocellulosic substrates, among proteins, total uronic acids, soluble sugars, crystalline cellulose, amorphous holocelluloses, and lignin. Only soluble sugars had a significant positive effect on biohydrogen production. Besides, methane potentials correlated negatively to the lignin contents and, to a lower extent, crystalline cellulose showed also a negative impact, whereas soluble sugars, proteins, and amorphous hemicelluloses showed a positive impact. These findings will help to develop further pretreatment strategies for enhancing both biohydrogen and methane production.

The evolution of the wake of a wind turbine contributes significantly to its operation and performance, as well as to those of machines installed in the vicinity. The inherent unsteady and three-dimensional aerodynamics of Vertical Axis Wind Turbines (VAWT) have hitherto limited the research on wake evolution. In this paper the wakes of both a troposkien and a H-type VAWT rotor are investigated by comparing experiments and calculations. Experiments were carried out in the large-scale wind tunnel of the Politecnico di Milano, where unsteady velocity measurements in the wake were performed by means of hot wire anemometry. The geometry of the rotors was reconstructed in the open-source wind-turbine software QBlade, developed at the TU Berlin. The aerodynamic model makes use of a lifting line free-vortex wake (LLFVW) formulation, including an adapted Beddoes-Leishman unsteady aerodynamic model; airfoil polars are introduced to assign sectional lift and drag coefficients. A wake sensitivity analysis was carried out to maximize the reliability of wake predictions. The calculations are shown to reproduce several wake features observed in the experiments, including blade-tip vortex, dominant and submissive vortical structures, and periodic unsteadiness caused by sectional dynamic stall. The experimental assessment of the simulations illustrates that the LLFVW model is capable of predicting the unsteady wake development with very limited computational cost, thus making the model ideal for the design and optimization of VAWTs.