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Structural health monitoring of piezoelectric structures by estimating energy conversion efficiency with capacitance measurements
No full textIn structures equipped with piezoelectric materials, the quantification of the efficiency of the energy conversion between mechanical and electrical domain (and vice versa) was already demonstrated to be a reliable feature for determining the presence of a structural damage. Usually, this efficiency is determined by means of vibration measurements to derive the value of the modal electro-mechanical coupling coefficient, which is the damage feature employed to calculate damage indexes. Nevertheless, in some cases, the estimation of this damage feature can be challenging because of different reasons, such as, e.g., non sufficient external excitation to the system, low values of the modal electro-mechanical coupling coefficient which makes its estimation uncertain and implies the need of shunting the piezoelectric elements with tailored electrical impedances. The present paper aims at showing that similar damage indexes can be estimated also by measuring capacitance trend as function of frequency for each piezoelectric element in the structure. This allows monitoring the structure without any need of vibration measurements and addition of external electric circuits used to shunt the piezoelectric elements, with significant simplification of the estimation procedure. Three different damage indexes are proposed, evidencing which of them are the most reliable for detecting the presence of the damage and getting information about its location. The method and the indexes are studied through numerical analyses and validated by means of an experimental campaign on a tailored set-up
Investigation of the effects of gamma radiation on solid polybutadiene-based propellants for space applications
No full textThis study examines how curing chemistry and additives tailor the response of hydroxy-terminated polybutadiene (HTPB) and polybutadiene (PB) binder systems to gamma irradiation at 25, 45, and 130 kGy (in air, at room temperature). Three formulations were evaluated: conventionally cured HTPB (H), antioxidant-stabilized HTPB (Ha), and photocured PB. Raman, FTIR, EPR, colorimetry, and optical microscopy reveal distinct formulation-dependent behaviors. H undergoes minimal changes at low doses but significant oxidation at 130 kGy. Although Ha progressively browns with doses, the antioxidant effectively limits chemical and mechanical degradation. The PB highly reactive network produces early discoloration, oxidation, and persistent multi-species radical formation
Pressure-induced crystallization and polymorphic transitions of polybutene-1: High-pressure PVT study
No full textIsotactic poly(1-butene) exhibits pressure-sensitive polymorphism, yet quantitative, phase-resolved volumetric evidence across processing-relevant pressures remains limited. High-pressure PVT dilatometry was employed to monitor specific-volume changes during controlled melt crystallization and remelting between 10 and 200 MPa at a fixed cooling rate. The resulting dilatometric fingerprints enable phase attribution after crystallization under each pressure condition. At low pressures (≤60 MPa) crystallization proceeds predominantly to form II; in an intermediate window (approximately 75–100 MPa) hydrostatic pressure markedly accelerates the solid–solid II→I transformation during or shortly after crystallization, yielding form-I–dominated structures. At higher pressures (≳110 MPa) signatures of form I′ emerge and intensify, and beyond ∼175 MPa the melting response is consistent with predominantly form I′. Across the series, specific volume of the solid phase follows the expected order (VI≲VIjavax.xml.bind.JAXBElement@2330adc
Real-Time Optimal Control of High-Dimensional Parametrized Systems by Deep Learning-Based Reduced Order Models
No full textSteering a system towards a desired target in a very short amount of time is a challenging task from a computational standpoint. Indeed, the intrinsically iterative nature of optimal control problems requires multiple simulations of the state of the physical system to be controlled. Moreover, the control action needs to be updated whenever the underlying scenario undergoes variations, as it often happens in applications. Full-order models based on, for example, the Finite Element Method, do not meet these requirements due to the computational burden they usually entail. On the other hand, conventional reduced order modeling techniques, such as the Reduced Basis method, despite their rigorous construction, are intrusive, rely on a linear superimposition of modes, and lack efficiency when addressing nonlinear time-dependent dynamics. In this work, we propose a non-intrusive Deep Learning-based Reduced Order Modeling (DL-ROM) technique for the rapid control of systems described in terms of parametrized PDEs in multiple scenarios. In particular, optimal full-order snapshots are generated and properly reduced by either Proper Orthogonal Decomposition or deep autoencoders (or a combination thereof) while feedforward neural networks are exploited to learn the map from scenario parameters to reduced optimal solutions. Nonlinear dimensionality reduction, therefore, allows us to consider state variables and control actions that are both low-dimensional and distributed. After (i) data generation, (ii) dimensionality reduction, and (iii) neural networks training in the offline phase, optimal control strategies can be rapidly retrieved in an online phase for any scenario of interest. The computational speedup and the extremely high accuracy obtained with the proposed approach are finally assessed on different PDE-constrained optimization problems, ranging from the minimization of energy dissipation in incompressible Navier–Stokes flows to the thermal active cooling in heat transfer
Hybrid Energy Storage Systems in Rail Transport
No full textAs of now, decarbonization is a central theme. In the European context, 40% of railway lines are operated by diesel trains. Among countries such as Italy, Germany or UK, even values as high as 60% are reached. In order to successfully achieve the 2030 and 2050 targets, in the past it has been considered to electrify all remaining lines. Hybrid trains, however, are an alternative to this. In this chapter, solutions for Hybrid Energy Storage Systems in rail transport will be discussed
Caratterizzazione sismica di chiller isolati con sistemi anti-vibranti
No full textAs well established, maintaining the operational integrity and safety of key infrastructure during seismic events is of
paramount importance. One requirement is the seismic protection of non-structural components and machinery, such
as HVAC (Heating, Ventilation, and Air Conditioning) equipment, Generators and UPS (Uninterruptible Power Supply)
systems. The paper is focused on the analysing seismic qualification methodologies, relevant standard and the current
normative for seismic design of non-structural elements and equipments. Experimental investigations with a triaxial
seismic table on an industrial chiller are briefly presented. Finally, the results of the simplified theoretical models
developed to predict the amplification factor of equipment isolated with anti-vibration supports are discusse