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Abstract In this work, a multi-variable multi-objective methodology aimed to perform the validation of the thermodynamic model has been applied to the Capstone C30 micro gas turbine. The methodology is based on a genetic optimization algorithm, where decision variables and objectives are set depending on available experimental data. The results of the studied case highlight the capability of the method to point out some experimental data inconsistencies and that it can lead to a consistency thermodynamic reconstruction of the micro turbine behaviour.

With reference to a classical wet tank equipped with a wastewater submersible pump, in this research, an advanced numerical model has been used in order to obtain the optimal pump scheduling of on/off operation and variable pump speed. Then, in order to evaluate the time decay of pump performances, the mechanical wear has been artificially simulated and the performance curves have been experimentally obtained for different rotational speeds. Finally, the benefits, as well as the feasibility, of pump scheduling have been evaluated for differing operating conditions. According to the results, the optimal pump scheduling achieves large energy savings up to 43%, for soft mechanical wear. If the mechanical wear is considered, the energy savings are large as well, between 35.60% and 26.70%, for medium and hard mechanical wear, respectively. On the other hand, the limitation of such a strategy has been highlighted: the feasibility of pump scheduling is limited by the elevation of the downstream tank. According to the results, energy savings can be achieved until the elevation of the downstream tank is 67% of the pressure head at the best efficiency point, whereas such percentage decreases to 50% for hard mechanical wear. Finally, the results show that plant efficiency is strongly affected by the mechanical wear: an accurate maintenance of the pumping system is therefore recommended in order to attenuate the time decay of pump performances.

The road network design problem is widely studied in the literature, both in urban and rural areas; most papers deal with the solution algorithms and with the mathematical formulation of the problem. The road network design problem is NP-hard and is very difficult to solve in acceptable computing times for real-scale networks. In urban areas, the objective of the design is usually the minimisation in total travel time on the network, while in rural areas it is usually a sum of total travel time and total (i.e. construction and maintenance) road costs. Very few papers consider other terms in the objective function and/or propose a multicriteria approach. In our best knowledge, no papers consider as objective of the design to minimise the fuel consumption, even if it is an actual objective of road network planning and design. In this paper, we compare the results obtained by solving some road network design problems adopting the classic objective functions and adopting as objective the minimisation in fuel consumptions on the network. In order to obtain this result, in the paper a fuel consumption function is proposed, based on CORINAIR models and depending on the vehicle fleet of the study area; this function is used both for estimating the reduction in fuel consumption due to the design obtained with the classic objective functions and for designing the road network using as objective function the total consumption on the network. The results obtained with these approaches are compared in terms of fuel consumed and total travel time spent on the network. The minimisation in fuel consumption is very important since greenhouse gas emissions and air pollutants are directly related to the consumption. Initial tests highlighted that the results obtained with the two different approaches are more significant in rural areas, where higher average flow speeds may produce higher consumption, according to the CORINAIR models.

A double-null configuration is being considered for the EU-DEMO, due to its potential benefits for power exhaust arising from the use of two active divertors and magnetically disconnected low- and high-field sides. Using systematic parameter scans in fluid simulations, we have investigated the divertor power exhaust in the EU-DEMO in a connected double-null configuration, and compared the edge plasma properties to those obtained in a single-null configuration under detached conditions anticipated for reactor operation. Neglecting drift effects and kinetic behaviour of the neutrals, no clear benefits of the double-null configuration could yet be identified for the radiation pattern and power mitigation on open field lines. Future work should address the aforementioned physics as well as the effect of the additional X-point on core radiation.

This paper proposes a stock dynamic sizing optimization under the Logistic 4.0 environment. The safety stock is conceived to fill up the demand variability, providing continuous stock availability. Logistic 4.0 and the smart factory topics are considered. It focuses on vertical integration to implement flexible and reconfigurable smart production systems using the information system integration in order to optimize material flow in a 4.0 full-service approach. The proposed methodology aims to reduce the occurring stock-out events through a link among the wear-out items rate and the downstream logistic demand. The failure rate items trend is obtained through life-cycle state detection by a curve fitting technique. Therefore, the optimal safety stock size is calculated and then validated by an auto-tuning iterative modified algorithm. In this study, the reorder time has been optimized. The case study refers to the material management of a very high-speed train.

A Sustainable Urban Mobility Plan (SUMP) is a strategic (long period) transportation plan aimed to improve welfare of both people and workers living in the city as well as in its surrounding area. Compared to “traditional” urban transportation plans, SUMP moves the focus from traffic (vehicles) to people with significant advancements in the direction of a sustainable mobility jointly with the quality of life. According to the recent European Guidelines, this type of strategic plan has to be built on existing planning practices and take due consideration: the integration, the participation, and evaluation. Starting from these considerations, in absence of a detailed national guideline implementing SUMP, the aim of this paper was to apply an innovative theoretical decision-making approachfor the development of the Naples (Italy) SUMP. This case study appears to be interesting because of the specificity of Naples, that is the third largest Italian city and metropolitan area with the highest population density. In 2016, the city of Naples has efficiently concluded and ratified a first formalization of acts: 'The analysis of mobility system' and ‘The statement of strategic objectives