The charged current production of long-lived heavy neutrinos at the LHC can use a prompt charged lepton for triggering the measurement of the process. However, in order to fully characterize the ...heavy neutrino interactions, it is necessary to also probe Higgs or
Z
mediated neutral current production. In this case the charged lepton is not available, so other means of triggering are required. In this work, we explore the possibility of using a vector boson fusion trigger in the context of a GeV-scale Type I Seesaw model. We consider a minimal model, where both Higgs and
Z
-mediated contributions produce one heavy neutrino, as well as an extended model where the Higgs can decay into two heavy ones. Both scenarios are tested through displaced dilepton and displaced multitrack jet searches.
A
bstract
RADES (Relic Axion Detector Exploratory Setup) is a project with the goal of directly searching for axion dark matter above the 30
μ
eV scale employing custom-made microwave filters in ...magnetic dipole fields. Currently RADES is taking data at the LHC dipole of the CAST experiment. In the long term, the RADES cavities are envisioned to take data in the BabyIAXO magnet. In this article we report on the modelling, building and characterisation of an optimised microwave-filter design with alternating irises that exploits maximal coupling to axions while being scalable in length without suffering from mode-mixing. We develop the mathematical formalism and theoretical study which justifies the performance of the chosen design. We also point towards the applicability of this formalism to optimise the MADMAX dielectric haloscopes.
► The control problem of a solar power plant with DCS (ACUREX) is discussed. ► A new practical NMPC to regulate the temperature of solar power plants is presented. ► Stability and robustness are ...guaranteed by a Lyapunov function approach. ► The proposed NMPC algorithm has a low computational cost. ► Case studies show the system performance with different model uncertainties.
This paper presents the application of a Nonlinear Model Predictive Controller (NMPC) to a distributed solar collector field. The control technique is basically similar to Dynamic Matrix Control (DMC) but in the proposed approach a nonlinear model of the process is directly used without linearization of the process model involved in the control strategy. Moreover, a modified Practical Nonlinear Model Predictive Controller (PNMPC) algorithm adapted to solar plant is developed in this work. To include robustness of stability against uncertainties in the NMPC algorithm, a candidate Lyapunov function is included in the cost function. The main purpose of the controller is to manipulate the oil flow rate to maintain the field outlet temperature in the desired reference value and attenuate the disturbances effects. The simulated process used is a distributed parameter model, while for the prediction a lumped parameter model with time delay was considered.
Here, a measurement with high statistics of the differential energy spectrum of light elements in cosmic rays, in particular, of primary H plus He nuclei, is reported. The spectrum is presented in ...the energy range from 6 to 158 TeV per nucleus. Data was collected with the High Altitude Water Cherenkov (HAWC) Observatory between June 2015 and June 2019. The analysis was based on a Bayesian unfolding procedure, which was applied on a subsample of vertical HAWC data that was enriched to 82% of events induced by light nuclei. To achieve the mass separation, a cut on the lateral age of air shower data was set guided by predictions of CORSIKA/QGSJET-II-04 simulations. The measured spectrum is consistent with a broken power-law spectrum and shows a kneelike feature at around E = 24.0$^{+3.6}_{-3.1}$ TeV , with a spectral index γ = -2.51 ± 0.02 before the break and with γ = -2.83 ± 0.02 above it. The feature has a statistical significance of 4.1σ. Within systematic uncertainties, the significance of the spectral break is 0.8σ.
The present work has been conducted in order to develop a novel approach to predict the inhomogeneous flow of a 20MnCr5 steel during an axisymmetric hot compression test, by using the element-free ...Galerkin (EFG) method under a differential constitutive description. The governing equations have been solved on the basis of the EFG global weak formulation. A detailed explanation concerning the characteristics inherent to the application of the EFG method to this problem, has also been provided. Furthermore, a return mapping algorithm for the solution of associative von Mises inelastic problems, has been formulated for the differential constitutive description employed in this communication, namely, a differential return mapping algorithm (DRMA). The feasibility and suitability of the EFG method for solving the axial compression problem has been shown by comparing its results with a FEM based solution employing a simple constitutive description. The reliability of the proposed DRMA has been demonstrated by a comparison of a homogeneous deformation numerical test with the experimental and direct integration results reported in a previous communication. Finally, the EFG model has been used to predict the stress, strain and volume fraction recrystallized distributions under steady and transient nominal strain rate and temperature deformation conditions. These parametric studies have been carried out by considering the differential constitutive description, but also a conventional integrated constitutive model of a 20MnCr5 steel. The results have revealed the suitability of the EFG formulation under the proposed DRMA, for predicting the performance of an axisymmetric hot compression test. The differences between the use of differential and integrated constitutive descriptions on the performance of hot-working processes under inhomogeneous deformation conditions, have also been evidenced in this research work.
•A differential constitutive description-based hot-compression model has been proposed.•The numerical solutions have been derived by means of the element-free Galerkin method.•A novel differential return mapping algorithm (DRMA) has been developed.•The DRMA was developed by computing the flow stress into an implicit difference scheme.•Notable differences were found with solutions based on integrated constitutive descriptions.
The experimental flow stress curves of structural steels obtained from axisymmetric compression tests conducted under hot-working conditions very often include the frictional effects present at the ...tool/specimen interface. Such effects have a significant influence on the flow stress and therefore, should be corrected prior to any quantitative analysis aimed at determining the constitutive description of these materials. Commonly, such a correction is carried out by assuming a constant friction coefficient (μ) or friction factor (m) independent of deformation conditions, which is an unrealistic approach. The present investigation analyzes experimentally the frictional effects that occur when steel is deformed under axisymmetric compression conditions in the temperature range of 850 to 1200 °C at a strain rate of 0.1 s
−1
and applied effective strains of 1, employing cylindrical samples with an initial diameter to initial height ratio (d
0
/h
0
) in the range of 0.5 to 2. Finite element modeling (FEM), as well as element-free Galerkin modeling (EFGM), have been employed for the analysis and prediction of the von Mises stress distribution, barreling and amount of metal folding undergone by the compression specimens. It has been shown that the increase in flow stress due to frictional effects can be corrected on the basis of either μ or m, by assuming that these parameters vary in the course of plastic deformation and are strongly dependent on deformation temperature. A novel procedure for the systematic correction of the flow stress curves, taking into consideration the changes in friction conditions during plastic deformation, has been proposed.
•The combination of a thermal desalination plant with a greenhouse is studied.•The proposed case of study is based on two real facilities located in Almería.•Dynamic models of both facilities and ...real meteorological data have been used.•A distributed controller is proposed for the efficient management of the system.•The results demonstrate the improvements achievable through the developed approach.
The scarcity of water experienced in Almería (south-eastern Spain), and in Mediterranean countries generally, has the potential to compromise one of its main economic drivers – agriculture. A possible solution is to combine thermal desalination technologies with crop cultivation. Accordingly, this paper proposes a distributed model predictive controller for the efficient operation of a distributed energy system comprising a solar-powered membrane distillation facility and a greenhouse, which is the most widespread type of crop cultivation in this region. The controller is in charge of calculating the optimal feed flow rates for each of the membrane distillation modules included in the desalination facility, according to the water requirements of the greenhouse and the thermal energy consumption of the membrane distillation plant (one of the main weak points of the technology). Simulation results using models for two real facilities located in Almería are presented; they show how the proposed distributed approach is able to manage industrial-scale plants in an optimal way. In addition, automatic operation is compared with manual operation (a non-optimal one), showing that the operation’s thermal efficiency can be improved by 5 % when applying the proposed technique, while satisfying the water demand. This means important thermal energy savings of around 50 MWh/season less thermal energy consumption for an 8 ha cultivation area.
The use of solar thermal systems to produce heat for industrial processes is a feasible option that is gaining increasing interest in recent years as an initiative toward the zero-carbon energy ...future. This technology has a place in different processes, yet there is still no consensus on the main methods for sizing or controlling. The design requires the use of specific techniques due to the inconstant nature of solar energy as well as the heterogeneity of some industrial thermal demands. Nevertheless, despite starting from a particular system’s design, the dynamic together with the hybrid and nonlinear behavior of the processes involved require adequate control techniques to provide the energy in a usable form and keep the system operating close to the design specifications. This paper presents a literature review concerning research works that address the design and control of solar thermal systems used in industrial contexts. The main objective is to analyze the different techniques used and to highlight their limits, usefulness, and the various industrial sectors where they were applied. The results of this analysis can be seen as a decision-making tool to select the most appropriate design or control strategy for these applications. It has been found that control techniques such as model predictive control can improve key performance metrics in daily operation. However, further development on these kinds of techniques and in holistic optimization methods that exploit the synergies between the operational and design phases is required.
•Design and control methods for solar thermal systems used in industries are reviewed.•The barriers and usefulness of each technique identified are analyzed.•The analysis results in a decision-making tool to select the most appropriate method.•Optimization-based design outperforms the other techniques for heterogeneous demands.•Advanced controllers can play a role due to the nonlinear system’s behavior.
We analyze the quantum entanglement between opposite spin projection electrons in the ground state of the Anderson impurity model. In this model, a single level impurity with intralevel repulsion U ...is tunnel coupled to a free electron gas. The Anderson model presents a strongly correlated many body ground state with mass enhanced quasiparticle excitations. We find, using both analytical and numerical tools, that the quantum entanglement between opposite spin projection electrons is a monotonic universal function of the quasiparticle mass enhancement Z in the Kondo regime. This indicates that the interaction induced mass enhancement, which is generally used to quantify correlations in quantum many body systems, could be used as a measure of entanglement in the Kondo problem.
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