2,063 research outputs found
Il porto di Genova tra il 1960 e il 1970 nelle fotografie di Ferdinando Magri
No full textCatalogo della mostra "Il porto di Genova tra il 1960 e il 1970 nelle fotografie di Ferdinando Magri". La mostra e i contributi in volume mettono in risalto come la fotografia di Ferdinando Magri abbia saputo catturare il periodo di profondo cambiamento tecnico, fisico ed economico che il porto di Genova ha attraversato tra gli anni sessanta e settanta
Il commissariamento degli enti locali per condizionamenti o infiltrazioni della criminalità organizzata
No full textIl contributo analizza criticamente la disciplina dello scioglimento dei consigli comunali e provinciali per infiltrazioni o condizionamenti della criminalità organizzata di tipo mafioso, di cui all'art. 143 del D.lgs. n. 267/2000. Ne esamina la storia, i rapporti con le norme costituzionali e con la CEDU, l'interpretazione della Corte costituzionale e della giurisprudenza amministrativa, le prospettive di riforma
Gradient-free optimization of chaotic acoustics with reservoir computing
No full textGradient-based optimization of chaotic acoustics is challenging for a threefold reason: (i) first-order perturbations grow exponentially in time; (ii) the statistics of the solution may have a slow convergence; and (iii) the time-averaged acoustic energy may physically have discontinuous variations, which means that the gradient does not exist for some design parameters. We develop a versatile optimization method, which finds the design parameters that minimize time-averaged acoustic cost functionals, and overcomes the three aforementioned challenges. The method is gradient-free, model-informed, and data-driven with reservoir computing based on echo state networks. First, we analyze the predictive capabilities of echo state networks in thermoacoustics both in the short- and long-time prediction of the dynamics. We find that both fully data-driven and model-informed architectures are able to learn the chaotic acoustic dynamics, both time-accurately and statistically. Informing the training with a physical reduced-order model with one acoustic mode markedly improves the accuracy and robustness of the echo state networks, while keeping the computational cost low. Echo state networks offer accurate predictions of the long-time dynamics, which would be otherwise expensive by integrating the governing equations to evaluate the time-averaged quantity to optimize. Second, we couple echo state networks with a Bayesian technique to explore the design thermoacoustic parameter space. The computational method is minimally intrusive because it requires only the initialization of the physical and hyperparameter optimizers. Third, we find the set of flame parameters that minimize the time-averaged acoustic energy of chaotic oscillations, which are caused by the positive feedback with a heat source, such as a flame in gas turbines or rocket motors. These oscillations are known as thermoacoustic oscillations. The optimal set of flame parameters is found with the same accuracy as brute-force grid search but with a convergence rate that is more than one order of magnitude faster. This work opens up new possibilities for nonintrusive (“hands-off”) optimization of chaotic systems, in which the cost of generating data, for example, from high-fidelity simulations and experiments, is high
Dispersionless integrable equations as coisotropic deformations: extensions and reductions
No full textOptimisation of chaotically perturbed acoustic limit cycles
No full textIn an acoustic cavity with a heat source, the thermal energy of the heat source can be converted into acoustic energy, which may generate a loud oscillation. If uncontrolled, these acoustic oscillations, also known as thermoacoustic instabilities, can cause mechanical vibrations, fatigue and structural failure. The objective of manufacturers is to design stable thermoacoustic configurations. In this paper, we propose a method to optimise a chaotically perturbed limit cycle in the bistable region of a subcritical bifurcation. In this situation, traditional stability and sensitivity methods, such as eigenvalue and Floquet analysis, break down. First, we propose covariant Lyapunov analysis and shadowing methods as tools to calculate the stability and sensitivity of chaotically perturbed acoustic limit cycles. Second, covariant Lyapunov vector analysis is applied to an acoustic system with a heat source. The acoustic velocity at the heat source is chaotically perturbed to qualitatively mimic the effect of the turbulent hydrodynamic field. It is shown that the tangent space of the acoustic attractor is hyperbolic, which has a practical implication: the sensitivities of time-averaged cost functionals exist and can be robustly calculated by a shadowing method. Third, we calculate the sensitivities of the time-averaged acoustic energy and Rayleigh index to small changes to the heat-source intensity and time delay. By embedding the sensitivities into a gradient-update routine, we suppress an existing chaotic acoustic oscillation by optimal design of the heat source. The analysis and methods proposed enable the reduction of chaotic oscillations in thermoacoustic systems by optimal passive control. Because the theoretical framework is general, the techniques presented can be used in other unsteady deterministic multi-physics problems with virtually no modification
Coisotopic deformations of associative algebras and dispersionless integrable hierarchies
No full textThe paper is an inquiry of the algebraic foundations of the theory of dispersionless integrable hierarchies. It stands out for the idea of interpreting these hierachies as equations of coisotropic deformations for the structure constants of certain associative algebras
- …
