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Energy consumption is now one of the most important issues for network carriers, since the majority of the energy needed for their operation is consumed in the wireless access and optical transport networks. The continuous growth in the wireless customers and traffic volumes and the consequent energy demand on modern carriers’ broadband infrastructures require reconsidering their energy efficiency, by starting from the formulation of new, more complete and representative network models that should become the foundations for modern energy-aware control plane architectures. Accordingly, this work presents a novel comprehensive energy model for next-generation wireless access-over-optical-transport networks characterized by hybrid power systems (i.e., multiple dynamically available power sources). The objective is to identify the energy-related information that need to be handled at the control plane layer to support energy-aware networking practices. Such information can be made available to suitable energy-aware routing and wavelength assignment algorithms that may exploit them to optimize the overall network energy-consumption and reducing the associated carbon footprint. The proposed model may be taken as a reference for the implementation of new energy-aware control plane protocols (routing and signaling) that make use of power-related considerations to achieve energy-efficiency and energy-awareness in wavelength-routed network infrastructures. Peer Reviewed

The study of neutron-induced reactions is of high relevance in a wide variety of fields, ranging from stellar nucleosynthesis and fundamental nuclear physics to applications of nuclear technology. In nuclear energy, high accuracy neutron data are needed for the development of Generation IV fast reactors and accelerator driven systems, these last aimed specifically at nuclear waste incineration, as well as for research on innovative fuel cycles. In this context, a high luminosity Neutron Time Of Flight facility, n_TOF, is operating at CERN since more than a decade, with the aim of providing new, high accuracy and high resolution neutron cross-sections. Thanks to the features of the neutron beam, a rich experimental program relevant to nuclear technology has been carried out so far. The program will be further expanded in the near future, thanks in particular to new highflux experimental area, now under construction.

The $^{238}$U to $^{235}$U fission cross section ratio has been determined at n_TOF up to $\sim$1 GeV, with two different detection systems, in different geometrical configurations. A total of four datasets have been collected and compared. They are all consistent to each other within the relative systematic uncertainty of 3-4%. The data collected at n_TOF have been suitably combined to yield a unique fission cross section ratio as a function of the neutron energy. The result confirms current evaluations up to 200 MeV. A good agreement is also observed with theoretical calculations based on the INCL++/Gemini++ combination up to the highest measured energy. The n_TOF results may help solving a long-standing discrepancy between the two most important experimental dataset available so far above 20 MeV, while extending the neutron energy range for the first time up to $\sim$1 GeV.

In this paper, an optimal power flow problem is formulated in order to minimize the total operation cost by considering real-time pricing in DC microgrids. Each generation resource in the system, including the utility grid, is modeled in terms of operation cost, which combines the cost-efficiency of the system with the demand response requirements of the utility. By considering the primary (local) control of the grid-forming converters of a microgrid, optimal parameters can be directly applied to the control of this level, thus achieving higher control accuracy and faster response. The optimization problem is solved in a heuristic way by using genetic algorithms. In order to test the proposed algorithm, a six-bus droop-controlled DC microgrid is used as a case-study. The obtained simulation results show that under variable renewable generation, load, and electricity prices, the proposed method can successfully dispatch the resources in the microgrid with lower total operation costs.

We present a simple mathematical model of glassy dynamics seen as a random walk in a directed, weighted network of minima taken as a representation of the energy landscape. Our approach gives a broader perspective to previous studies focusing on particular examples of energy landscapes obtained by sampling energy minima and saddles of small systems. We point out how the relation between the energies of the minima and their number of neighbors should be studied in connection with the network's global topology, and show how the tools developed in complex network theory can be put to use in this context.