This thesis investigates the statistical aspects of intermittent deformation during martensitic phase transitions in shape memory alloys, proposing a conceptual analogy between such solid-state phenomena and turbulence in fluid dynamics. The analysis focuses on a single Cu-Al-Ni crystal, for which both the displacement field and the right deformation gradient tensor are available, experimentally acquired during the cooling phase. By employing compact finite difference schemes, the spatial derivative of the displacement field was estimated, thereby validating the accuracy of the available dataset. An energy-minimization-based algorithm was used to classify each pixel as martensitic or austenitic, enabling the local identification of phases. This classification allowed for the estimation of the martensitic volume fraction and the identification of the time steps (i.e., file pairs) corresponding to the most intense phase transitions. The core innovation of this work lies in the adaptation of structure functions—originally formulated in Kolmogorov’s 1941 theory—to the tensor representing the variations of the right deformation gradient tensor between successive states. The computed structure functions reveal spatial heterogeneities, characteristic scales, and preferential directions, clearly breaking the classical isotropy assumption. The analysis culminates in the study of deformation avalanches, interpreted as intermittent and collective events: both forward and reverse avalanches are identified, reinforcing the analogy with fluid turbulence, in which direct and inverse energy cascades are distinguished. The results suggest a connection between microstructural transformation phenomena in solids and turbulent dynamics in fluids, offering new perspectives toward a unified understanding of intermittency and complexity in heterogeneous physical systems.
La presente tesi indaga gli aspetti statistici della deformazione intermittente durante le transizioni di fase martensitiche in leghe a memoria di forma, proponendo un'analogia concettuale tra tali fenomeni solidi e la turbolenza in fluidodinamica. L’analisi si concentra su un singolo cristallo di Cu-Al-Ni, di cui si hanno a disposizione il campo di spostamento e il tensore gradiente di deformazione destro, acquisiti sperimentalmente durante la fase di raffreddamento. Attraverso l’impiego di schemi compatti alle differenze finite, si è stimata la derivata del campo di spostamento, validando così l’accuratezza del dataset disponibile. Un algoritmo basato sulla minimizzazione energetica ha permesso, distinguendo i pixel in fase martensitica da quelli in fase austenitica, la classificazione locale delle fasi. Si è allora proceduto con la stima della frazione volumetrica di martensite e l’identificazione degli istanti, quindi le coppie di file, rappresentanti le variazioni di fase più intense. Il nucleo innovativo del lavoro consiste nell’adattamento delle funzioni di struttura della teoria di Kolmogorov del 1941 al tensore rappresentante le variazioni del tensore gradiente di deformazione destro del materiale tra stati successivi. Le funzioni di struttura calcolate rivelano la presenza di eterogeneità spaziali, scale caratteristiche e direzioni preferenziali, violando l’ipotesi di isotropia classica. L’analisi culmina nello studio delle valanghe di deformazione, interpretate come eventi intermittenti e collettivi: vengono identificate valanghe dirette e inverse, suggerendo ancora una volta il parallelismo con la turbolenza fluidodinamica, in cui distinguono cascate energetiche dirette e inverse. I risultati suggeriscono una connessione tra fenomeni di trasformazione microstrutturale nei solidi e dinamiche turbolente nei fluidi, aprendo nuove prospettive per una comprensione unificata dell’intermittenza e della complessità in sistemi fisici eterogenei.
Turbolenza nei solidi? Aspetti statistici della deformazione intermittente nelle transizioni di fase martensitiche in leghe a memoria di forma
Cerbone, Francesca
2024/2025
Abstract
This thesis investigates the statistical aspects of intermittent deformation during martensitic phase transitions in shape memory alloys, proposing a conceptual analogy between such solid-state phenomena and turbulence in fluid dynamics. The analysis focuses on a single Cu-Al-Ni crystal, for which both the displacement field and the right deformation gradient tensor are available, experimentally acquired during the cooling phase. By employing compact finite difference schemes, the spatial derivative of the displacement field was estimated, thereby validating the accuracy of the available dataset. An energy-minimization-based algorithm was used to classify each pixel as martensitic or austenitic, enabling the local identification of phases. This classification allowed for the estimation of the martensitic volume fraction and the identification of the time steps (i.e., file pairs) corresponding to the most intense phase transitions. The core innovation of this work lies in the adaptation of structure functions—originally formulated in Kolmogorov’s 1941 theory—to the tensor representing the variations of the right deformation gradient tensor between successive states. The computed structure functions reveal spatial heterogeneities, characteristic scales, and preferential directions, clearly breaking the classical isotropy assumption. The analysis culminates in the study of deformation avalanches, interpreted as intermittent and collective events: both forward and reverse avalanches are identified, reinforcing the analogy with fluid turbulence, in which direct and inverse energy cascades are distinguished. The results suggest a connection between microstructural transformation phenomena in solids and turbulent dynamics in fluids, offering new perspectives toward a unified understanding of intermittency and complexity in heterogeneous physical systems.File | Dimensione | Formato | |
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2025_07_Cerbone_Tesi_01.pdf
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2025_07_Cerbone_Executive_Summary_02.pdf
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https://hdl.handle.net/10589/240273