Date of Award
2025
Degree Type
Dissertation
Degree Name
Doctor of Philosophy in Mechanical Engineering and Applied Mechanics
Department
Mechanical, Industrial and Systems Engineering
First Advisor
Sumanta Das
Abstract
This dissertation consists of 5 Chapters. Chapter 1 presents an interpretable machine learning (ML) approach for efficient response prediction of three-dimensional (3D)-printed metamaterials. However, developing such an ML-based model requires a large consistent, representative, balanced, and complete dataset. To this extent, an experimentally validated finite element analysis (FEA) approach is implemented to generate 8096 non-self-intersecting re-entrant honeycomb structures by varying the mesoscale geometrical features to obtain the corresponding Poisson’s ratios. This dataset is leveraged to develop a feed-forward multilayer perceptron-based predictive model. The developed ML model shows excellent predictive efficacy on the unseen test dataset. Shapely additive explanation (SHAP) is then used for model interpretation. SHAP results show that the slant cell length is the dominant input feature dictating the model output whereas cell angle and vertical cell length show mixed trends signifying that other input features influence their effect on the model output. Moreover, cell thickness does not significantly influence the model output when compared to other input features. Overall, the integrated numerical simulation-experiment-interpretable ML-based predictive approach presented here can be leveraged to design and develop metamaterials for a wide range of engineering applications. Chapter 2 investigates a novel hybrid confinement strategy for concrete cylinders that combines carbon fiber-reinforced polymer (CFRP) wraps with re-entrant auxetic honeycomb structures to simultaneously enhance strength and ductility. Finite element analyses were conducted to evaluate the individual and combined effects of two key parameters: the number of auxetic core layers and the percentage of continuous carbon fibers (CCF) embedded within the auxetic geometry. Parametric simulations revealed that CFRP wraps significantly improve compressive strength, while auxetic cores - especially those with higher CCF content - enhance both strength and strain capacity. Hybrid configurations integrating CFRP wraps with auxetic cores outperformed both standalone systems. Notably, the configuration consisting of a re-entrant auxetic core sandwiched between two inner and two outer CFRP layers achieved a 221% increase in compressive strength and an 80% increase in strain capacity compared to unconfined concrete, along with a 50% improvement in strain capacity over a four-layer CFRP-wrapped specimen. While compressive strength gains plateaued at higher CFRP wrap densities, strain capacity continued to improve with auxetic core inclusion. This enhancement is attributed to the auxetic core’s unique lateral contraction behavior under axial load, which intensifies confinement pressure and delays tensile cracking. When combined with CFRP, the auxetic core acts as an adaptive interlayer that maintains continuous contact with concrete substrate, mitigating debonding and promoting more effective stress transfer. These findings demonstrate the effectiveness of auxetic-CFRP hybrid confinement in enhancing both strength and ductility, offering a promising approach for the development of resilient, damage-tolerant concrete systems for structural applications. Chapter 3 investigates the fluid-structure interaction (FSI) mechanisms and hydrostatic implosion behavior of metallic cylindrical tubes with varying geometrical and material configurations using advanced numerical simulations in LS-DYNA. Cylindrical shells made from aluminum 6061-T6, stainless steel 304, and titanium TC4 were modeled under external hydrostatic loading, with systematic variation of length-to-diameter (L/D) ratios from 2 to 5 and diameter-to-thickness (D/t) ratios from 20.32 to 50.80. The pressure-time histories, internal energy evolution, and peak overpressures were analyzed to characterize the dynamic collapse behavior and the intensity of fluid-structure coupling. Experimental validation was performed using aluminum cylinders with a length-to-diameter ratio (L/D) of 10.8 and a diameter-to-thickness ratio (D/t) of 28.57, demonstrating a strong correlation with numerical predictions. Results indicate that materials with higher stiffness and strength, such as titanium and stainless steel, exhibit delayed collapse, higher energy absorption, and stronger peak pressure waves compared to aluminum. Furthermore, geometric ratios significantly affect the mode of collapse and the FSI response, with higher L/D and lower D/t ratios leading to more complex buckling patterns and increased dynamic loading on the surrounding fluid. The study highlights the importance of understanding geometric sensitivity and material selection in implosions and structural failures in underwater applications, where implosion resilience and energy dissipation are critical. Chapter 4 performs a comprehensive numerical investigation into the dynamic behavior and fluid-structure interactions (FSI) of metallic cylinders undergoing hydrostatic collapse in semi-confined fluid environments using LS-DYNA. The model was validated against experimental data, demonstrating excellent agreement in critical collapse pressure, timing of collapse, as well as the magnitude and timing of successive water hammer pulses. Following validation, the study explores the in-fluence of material type (aluminum versus titanium), cylinder slenderness ratio (L/D), and confinement diameter on collapse behavior, pressure evolution, and fluid motion. Titanium cylinders, owing to their higher stiffness and yield strength, consistently exhibited sharper collapses, elevated water hammer pressures, and higher kinetic and strain energy accumulations compared to aluminum. Lower L/D ratios induced more abrupt collapses and higher-order buckling, while higher L/D ratios facilitated axisymmetric deformation with more gradual energy dissipation. Confinement diameter further modulated these trends, with larger fluid volumes enabling delayed collapse, intensified jet formation, and elevated fluid velocity magnitudes. The simulation results offer mechanistic insights into the coupling between structure and fluid, revealing that the interplay of geometry, material stiffness, and boundary confinement governs collapse-induced energy transfer. Full-field FSI provided deeper insight into collapse dynamics by capturing critical features - such as radial jetting, peak fluid velocities, and internal cavitation - not evident in pressure-time histories alone. Furthermore, owing to its ability to operate across a broad parametric space at low marginal cost, the validated model enables efficient generation of high-quality datasets for training machine-learning surrogates, thereby accelerating the predictive design optimization of underwater structures. Chapter 5 develops an experimentally validated multi-faceted fluid-structure interaction (FSI) model using LS-DYNA to investigate sequential sympathetic implosion of metallic cylinders in semi-confined underwater environments. The numerical model was first validated using experiments in which sequentially arranged aluminum cylinders underwent hydrostatic collapse in a semi-confined chamber, with transient pressure sensors capturing key response metrics. Numerical simulations successfully replicated the observed collapse sequence and matched the dynamic pressure-time response in both magnitude and timing, reinforcing confidence in the accuracy and predictive capability of the FSI framework. Following this successful validation, a series of parametric studies was conducted by varying the secondary cylinder’s length-to-diameter (L/D) ratio to investigate its influence on sympathetic implosion dynamics, energy absorption, and pressure wave evolution. Results show that increasing the L/D ratio of the secondary cylinder from 4 to 6 leads to earlier sympathetic collapse, greater than 14% increase in kinetic energy absorption, and strain energy surpassing that of the primary cylinder. Pressure recordings and FSI profiles reveal peak overpressures escalating by 10-15%, fluid jet velocities doubling (from ~65 to ~130 m/s), and more coherent pressure rebound patterns as slenderness increases. These findings elucidate key relationships such as higher L/D ratios accelerate energy transfer, amplify collapse intensity, and produce stronger, more focused pressure waves. Conversely, shorter cylinders exhibit delayed, impulsive collapse with reduced energy uptake. The insight into geometry-dependent buckling modes, energy partitioning, jetting behavior, and pressure-wave propagation enables strategic design of underwater assemblies to either mitigate or harness sympathetic implosions. The validated LS-DYNA ALE-based FSI model provides a reliable foundation for developing machine learning-driven design tools to efficiently assess and mitigate sympathetic collapse in submerged systems
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Recommended Citation
Oladipo, Bolaji, "MECHANICAL RESPONSE AND DEFORMATION MECHANISMS OF CONFINED CYLINDRICAL SYSTEMS UNDER VARYING LOADING SCENARIOS" (2025). Open Access Dissertations. Paper 4509.
https://digitalcommons.uri.edu/oa_diss/4509