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Reliability of Domestic Gas Flow Sensors with Hydrogen Admixtures
Full text linkStatic flow sensors (e.g., thermal gas micro electro-mechanical sensors—MEMS—and ultrasonic time of flight) are becoming the prevailing technology for domestic gas metering and billing since they show advantages in respect to the traditional volumetric ones. However, they are expected to be influenced in-service by changes in gas composition, which in the future could be more frequent due to the spread of hydrogen admixtures in gas networks. In this paper, the authors present the results of an experimental campaign aimed at analyzing the in-service reliability of both static and volumetric gas meters with different hydrogen admixtures. The results show that the accuracy of volumetric and ultrasonic meters is always within the admitted limits for subsequent verification and even within those narrower of the initial verification. On the other hand, the accuracy of the first generation of thermal mass gas flow sensors is within the limits of the verification only when the hydrogen admixture is below 2%vol. At higher hydrogen content, in fact, the absolute weighted mean error ranges between 3.5% (with 5%vol of hydrogen) and 15.8% (with 10%vol of hydrogen)
A Hybrid Deep Learning Approach for Modelling and Optimising Data Centre Energy Efficiency
No full textData Centres (DCs), the core of the ever-increasing economic and societal activities, are experiencing high energy consumption due to the rapidly growing demand for digital services, which leads to the largest DCs' operational costs and significant environmental and power security impacts. Hence, optimising their energy efficiency is a critical and top priority to ensure economic and environmentally sustainable DC management. However, prior heuristics and engineering-based solutions are inadequate due to the increasing physical complexity and sheer number of possible configurations, non-linear system interactions, and the growing monitoring of operational management data. Therefore, this paper develops a six-layered hybrid Convolutional Neural Network (CNN) and Long-Short-Term Memory (LSTM), called CNN-LSTM, a suitable data-driven Deep Learning (DL) model inspired by the human brain for effectively modelling the complex and plant performance and optimising DC efficiency. The proposed model uses CNN to capture complex parameter interactions and spatial pattern recognition and LSTM to capture temporal dependencies of the time series operational data to predict the next energy consumption value and optimise it using a cooling system fan speed controllable variable. The model was extensively trained and tested using actual operational management data obtained from the Enea High-Performance Computing (HPC) CRESCO6 cluster, Italy. 80% of the data was used for training, and the rest 20% for testing. According to the experimental results, it accurately predicts energy consumption every 15 minutes with an average Mean Absolute Error (MAE) of 0.0043. A sensitivity analysis optimisation strategy is also implemented using various cooling system fan speed set points. When the fan speed optimal set-point is automatically reduced by 50%, the energy consumption is optimised by an average of 0.0029 kWh with a 0.0039 MAE over the last 15 minutes of the testing set. Hence, this paper found that the proposed CNN-LSTM deep learning predictive model can effectively mimic actual DC operations and optimise efficiency. By simulating this model, DC operators can effectively manage and optimise their DC energy efficiency while reducing energy and environmental costs
On the radiation-induced polymerization of indene: from laboratory study to astrochemical implications
No full textThe radiation-induced polymerization of indene with a γ radiation source was studied at different dose rates (1, 2, 4, 6 kGy/h) and absorbed doses up to 400 kGy. The polymerization rate was determined through the thermogravimetric analysis and the spectrophotometric analysis of the irradiated indene solutions. With the two complementary methods the polymerization rates were determined for each dose rate. A mixed polymerization mechanism was ascertained involving either free radicals but also cations. In fact, the mixed mechanism was suggested as well by the n = 0.84 exponent of the dose rate in the polymerization kinetics equation and by the value of the radiation chemical yield Gp = G(−M) ≈ 103 molecules/100 eV. The infrared spectrum of the radiation-polymerized indene is analogous to the spectrum of a reference TiCl4-polyindene. However, the FT-IR spectrum of the former shows a couple of better defined and sharper infrared bands with respect to the latter, indicating a better structural regularity for the radio-polyindene. Since indene has been claimed as one of the potential polycyclic aromatic hydrocarbons (PAHs) present in the interstellar medium, our results suggest that it is likely that indene should be accompanied by -polyindene because of the monomer is very sensitive to the high energy radiation-induced polymerization
Innovative dud detection based on JET DT experience
No full textDT operations at JET gave a unique and invaluable opportunity to design, develop and test real-time controllers that will be applied in future burning plasma devices, as ITER and SPARC. Among them, the dud detector [L. Piron et al. 2019 Fusion Eng. Design 146 1364] is of primary importance since it allows to optimize the limited neutron and tritium budget consumptions. Such kind of a detector has been finalized and routinely used during DT experiments performed in 2021. In this work, we are proposing an innovative dud detector based on the experience gained during DT operation, namely add a metrics which supervises the H mode behaviour and allows redundancy on the input signals to cope with possible diagnostic and/or signal failures
Ambient humidity, the overlooked influencer of radioactivity measurements
No full textWhen verifying the validity of the exponential-decay law through 137 precise decay rate measurement series at various nuclear laboratories, minor violations have been observed in the shape of annual cycles in the residuals with different amplitudes and phase shifts. The timing and amplitude of these deviations have been compared with local weather data and it appears that ambient humidity is highly correlated with the observed instabilities in these radioactivity measurements. In fact, when compensating the residuals for a linear relationship with absolute humidity in air, most of the annual cycles are no longer statistically significant. As a result, the validity of the exponential-decay law can now be demonstrated with even higher fidelity
Luca Vitone: Monitoring of Four Living Canvases
No full text“Atmospheric” painting stands as a new frontier in contemporary art, presenting challenges and new considerations in museum practices. This article aims to analyze the possible evolution of four atmospheric paintings created by artist Luca Vitone during their transition from exhibition halls to the storage facilities of the MAXXI museum. The presence of active microbiological consortium raises question regarding the potential interaction these artworks may have with the surrounding environment. The year-long monitoring involved macroscopic and microscopic observation, spectrophotometric analyses, and cell vitality assessments using a bioluminometer. Additionally, the collected data were correlated with the prevailing microclimate within the storage. Indeed, the canvases underwent an evolution during their transfer to the storage; it was mainly the photosynthetic part of the consortium that underwent the greatest changes, resulting in changes in the color tones of the canvases. The viability of the cells in the consortium also underwent changes as indicated by measurements obtained with the bioluminometer. The monitoring has provided invaluable insights into the dynamic evolution of Vitone’s artworks and allowed the authors to hypothesize some strategies for the conservation of these types of artworks
Effect of 14.1 MeV Fusion Neutron Irradiation on YBCO Thin Films and Commercial REBCO Tapes
No full textThe design of new tokamak machines relying on the use of high temperature superconductors (HTS) is promoting the study of HTS properties at the operating conditions required by fusion applications. In particular, the interest in the damage induced by neutron irradiation on REBa2Cu3O7-δ (REBCO, RE = Y or lanthanide series), one of the most used family of HTS, has recently risen and several studies have been devoted to radiation hardness tests performed with ion irradiation or fission neutrons. In this work, the effect of neutron irradiation on YBCO films and commercial REBCO tapes was investigated using, for the first time, neutrons produced by the D-T fusion reaction. The experiment was carried out at ENEA-Frascati Neutron Generator (FNG) where a deuteron beam is accelerated up to 300 keV and directed on a tritiated target to produce a nearly isotropic 14.1 MeV neutron field via the T(d,n)α fusion reaction. Different YBCO films deposited through metal-organic decomposition (MOD) route on single crystals (SrTiO3 and LaAlO3) and REBCO commercial tapes, grown by pulsed laser deposition, were irradiated. Samples exposed to three fluences were compared with a maximum neutron fluence of 1.2·1014 cm-2. The properties of HTS materials were assessed before and after irradiation by means of different techniques. From these measurements, no significant effect on the considered properties was recognized indicating the robustness of films up to the explored irradiation fluences
Non-singular gravitational collapse through modified Heisenberg algebra
No full textWe study the effects of cut-off physics, in the form of a modified algebra inspired by Polymer Quantum Mechanics and by the Generalized Uncertainty Principle representation, on the collapse of a spherical dust cloud. We analyze both the Newtonian formulation, originally developed by Hunter, and the general relativistic formulation, that is the Oppenheimer–Snyder model; in both frameworks we find that the collapse is stabilized to an asymptotically static state above the horizon, and the singularity is removed. In the Newtonian case, by requiring the Newtonian approximation to be valid, we find lower bounds of the order of unity (in Planck units) for the deformation parameter of the modified algebra. We then study the behaviour of small perturbations on the non-singular collapsing backgrounds, and find that for certain range of the parameters (the polytropic index for the Newtonian case and the sound velocity in the relativistic setting) the collapse is stable to perturbations of all scales, and the non-singular super-Schwarzschild configurations have physical meaning
Proton-beam energy diagnostics by color-center photoluminescence imaging in LiF crystals: Implementation of multiple Coulomb scattering into an analytical Bragg-curve model
Full text linkLithium fluoride crystals are used to assess proton-beam energy spectra. Proton irradiation induces laser-active color centers in the crystal, whose density correlates with the absorbed dose. The spatial distribution of photoluminescence emitted by these color centers is exploited to estimate the proton-beam energy spectrum using an analytical Bragg-curve model. This study integrates the effects of multiple Coulomb scattering (MCS) into the model. At high enough energies, MCS leads to proton leakage through the crystal faces with a reduction in absorbed dose along the crystal length. The model incorporates MCS using an empirical approach based on Monte Carlo simulations
Involvement of Mitochondria in the Selective Response to Microsecond Pulsed Electric Fields on Healthy and Cancer Stem Cells in the Brain
Full text linkIn the last few years, pulsed electric fields have emerged as promising clinical tools for tumor treatments. This study highlights the distinct impact of a specific pulsed electric field protocol, PEF-5 (0.3 MV/m, 40 μs, 5 pulses), on astrocytes (NHA) and medulloblastoma (D283) and glioblastoma (U87 NS) cancer stem-like cells (CSCs). We pursued this goal by performing ultrastructural analyses corroborated by molecular/omics approaches to understand the vulnerability or resistance mechanisms triggered by PEF-5 exposure in the different cell types. Electron microscopic analyses showed that, independently of exposed cells, the main targets of PEF-5 were the cell membrane and the cytoskeleton, causing membrane filopodium-like protrusion disappearance on the cell surface, here observed for the first time, accompanied by rapid cell swelling. PEF-5 induced different modifications in cell mitochondria. A complete mitochondrial dysfunction was demonstrated in D283, while a mild or negligible perturbation was observed in mitochondria of U87 NS cells and NHAs, respectively, not sufficient to impair their cell functions. Altogether, these results suggest the possibility of using PEF-based technology as a novel strategy to target selectively mitochondria of brain CSCs, preserving healthy cells