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Efficient entropy-conserving/stable discontinuous Galerkin solution of the multicomponent compressible Euler equations
No full textThis paper presents the development of an efficient discontinuous Galerkin (dG) solver for the multicomponent compressible Euler equations. The method provides global entropy conservation/stability at the discrete level, contributing to the robustness of the computations, cf. [4,19]. The unsteady term of the governing equations is formulated for the conservative variables, while the spatial discretization is assembled from the L2-projection of the entropy variables [4,19] onto the dG function space, as suggested by Chan et al. [44] and Alberti et al. [35]. This approach requires numerical over-integration to ensure entropy conservation/stability, significantly degrading the computational performance. The Direct Enforcement of Entropy Balance (DEEB) proposed by Abgrall in [11] is implemented to avoid this. The DEEB consists of an explicit correction to the discretization to avoid unphysical entropy evolution. As high-order discretizations give rise to spurious oscillations at flow discontinuities, a directional shock-capturing term is added to the discretized equations. The performance of the solver is compared to alternative approaches, i.e., solving directly for the conservative or the entropy variables, by computing several onedimensional cases. The convergence of the numerical solution is also tested using the method of manufactured solutions (MMS). The interactions of a shock wave with a circular and a square inhomogeneity are finally considered, assessing the accuracy of the solver for reproducing complex two-dimensional phenome
Descrivere la migrazione artistica. Artemia (Archivio Teatrale Migrazioni Italia-America): un esempio di applicazione GIS alla storia dello spettacolo
No full textLa migrazione artistica è un fenomeno di grande rilievo nella storia culturale, caratterizzato dal trasferimento di artisti, opere e idee tra contesti geografici e temporali diversi, generatore di scambi e influenze reciproche. In questo contesto, la descrizione archivistica svolge un ruolo essenziale nel documentare, conservare e rendere accessibili le tracce di tali movimenti. Il saggio analizza la struttura e la concezione delle schede di compilazione del database Artemia (Archivio Teatrale Migrazioni Italia-America), evidenziando il dialogo tra Archivistica e Storia dello spettacolo e l’impatto dell’informatizzazione sulla gestione dei dati. In tal senso, Artemia può sviluppare una cooperazione internazionale con ICA/SLA per preservare e valorizzare gli archivi della migrazione artistica, promuovendo l’adozione di standard globali e la condivisione di risorse archivistiche per una più ampia accessibilità. Sono qui esaminati anche i punti di forza e le criticità degli strumenti tecnologici impiegati – ArcGIS (Esri italia) – rispetto agli obiettivi del progetto, sottolineando il necessario compromesso tra software, metodologie archivistiche e la complessità delle migrazioni artistiche. Il dialogo tra Archivistica e Storia dello spettacolo, si apre inevitabilmente a un terzo attore, l’informatica, provando a costruire un necessario, quanto urgente, linguaggio ‘ponte’ tra discipline diverse
Machine learning for prompt estimation of macroseismic intensity from seismometric data in Italy
No full textNew aza[6]helicenes: Synthesis, enantiomeric separation, (chir)optical properties and DFT calculations
No full textHerein, we report the design, synthesis, and characterization of new aza[6]helicene derivatives, focusing on their photophysical and chiroptical properties. The target compounds were synthesized in good overall yields (43%– 71%) through a four-step sequence starting from quinoline–3–carbaldehyde. Their structures were confirmed by NMR and FT–IR spectroscopies, mass spectrometry, and single-crystal X–ray diffraction analysis. Photophysical investigations revealed a noticeable UV/Vis absorption and a fluorescence emission in the blue region of the electromagnetic spectrum. The racemic helicenes were successfully separated by chiral HPLC, resulting in P– and M–enantiomers in excellent optical purity (> 99.5% ee). These enantiomers exhibited large specific optical rotations
(e.g., +2350–3200 for the P–enantiomer at λ = 589 nm) and remarkable electronic circular dichroism
(ECD) signals. Density functional theory (DFT) was used to clarify the structure–property relationships and to
reproduce the experimental observations with good accuracy. The comparative analysis between computational
results and experimental data highlights the potential of these N–heteroaromatic scaffolds as organic small–
molecules for applications as blue-emitting chiral dopants in OLED devices and as hole-transport units
Asymmetric Anticipatory Emotions Underlie Risk and Time Preferences
No full textWe are often preoccupied with the future, experiencing dread at the thought of future misery and savoring the thought of future pleasure. Prior lab studies have found that these anticipatory emotions influence decision-making. In this article, using economic survey data to estimate individual differences in anticipatory emotions, we find that the tendency to feel displeasure from anticipating future losses outweighs the pleasure from anticipating equal gains. We then relate asymmetries in anticipatory emotions to key economic preferences, finding that people with more strongly asymmetric anticipatory emotions are more risk-avoidant (because they obtain more disutility from contemplating downside risk) and more impatient (because they want to minimize the time spent contemplating risks). We conclude by considering how asymmetries in anticipatory emotions may be linked to a range of intertemporal and risky choice phenomena. Overall, our framework explains why risk-avoidance and impatience are linked and we provide suggestive evidence for this explanation
Forecasting high-granular air passenger demand flows: An integrated modeling framework applied to the Italian airport system
No full textDemand forecasting is a pivotal aspect of the multifaceted business of airlines and airports, significantly influencing long-term strategic decisions. For airports, accurate traffic forecasts are particularly crucial for aligning infrastructure capacity with future needs, necessitating tailored approaches to capture complex demand dynamics. This paper proposes a novel modeling framework to formulate high-granular itinerary-level demand forecasts, ultimately ensuring robust system-level predictions. The modeling framework leverages a state-of-the-art integrated demand modeling coupled with a customized scenario analysis tool. We demonstrate the validity of the proposed approach in supporting airport strategic planning by reporting the outcomes of its application on the Italian airport system, formulating traffic forecasts up to 2035 and testing predictive ability based on actual traffic data for 2024. We showcase the adaptability of the framework in addressing diverse challenges that decision-makers and policymakers will face in the near future, such as implementing policies to support the aviation industry’s transition to net-zero emissions
