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The safeguard of power equipments is assuming a major role in the deregulated electricity market, where a malfunctioning power system could be responsible for serious damages to a large number of system operators having access to the shared energy resource. In this context thermal monitoring of power cables represents a key issue in evaluating the risks associated with a given load management policy especially during emergency conditions. In particular this demands for reliable assessment models that should be able to predict the transient thermal behaviour when the load exceeds the nameplate value. In this connection the application of both simplified and detailed power cable thermal models is often complicated by the presence of uncertainties affecting the tolerances of the input data. The effect of these uncertainties could influence the final solution to a considerable extent. A comprehensive tolerance analysis is therefore required in order to incorporate the effect of data uncertainties into the thermal modelling process. To address this problem, in the paper the employment of interval mathematic is proposed. Several numerical results are presented and discussed in order to assess the effectiveness of the proposed methodology which offer a rough qualitative insight of the solution in a very short time, comparable to the time required for a deterministic numerical simulation.

The safeguard of power equipments is assuming a major role in the deregulated electricity market, where a malfunctioning power system could be responsible for serious damages to a large number of system operators having access to the shared energy resource. In this context thermal monitoring of power cables represents a key issue in evaluating the risks associated with a given load management policy especially during emergency conditions. In particular this demands for reliable assessment models that should be able to predict the transient thermal behaviour when the load exceeds the nameplate value. In this connection the application of both simplified and detailed power cable thermal models is often complicated by the presence of uncertainties affecting the tolerances of the input data. The effect of these uncertainties could influence the final solution to a considerable extent. A comprehensive tolerance analysis is therefore required in order to incorporate the effect of data uncertainties into the thermal modelling process. To address this problem, in the paper the employment of interval mathematic is proposed. Several numerical results are presented and discussed in order to assess the effectiveness of the proposed methodology which offer a rough qualitative insight of the solution in a very short time, comparable to the time required for a deterministic numerical simulation.

Abstract The dynamics of isolated-photon plus two-jet production in pp collisions at a centre-of-mass energy of 13 TeV are studied with the ATLAS detector at the LHC using a dataset corresponding to an integrated luminosity of 36.1 fb−1. Cross sections are measured as functions of a variety of observables, including angular correlations and invariant masses of the objects in the final state, γ + jet + jet. Measurements are also performed in phase-space regions enriched in each of the two underlying physical mechanisms, namely direct and fragmentation processes. The measurements cover the range of photon (jet) transverse momenta from 150 GeV (100 GeV) to 2 TeV. The tree-level plus parton-shower predictions from Sherpa and Pythia as well as the next-to-leading-order QCD predictions from Sherpa are compared with the measurements. The next-to-leading-order QCD predictions describe the data adequately in shape and normalisation except for regions of phase space such as those with high values of the invariant mass or rapidity separation of the two jets, where the predictions overestimate the data.