Browsing by Author "Bortolan Neto, L"

Now showing 1 - 8 of 8
  • No Thumbnail Available
    Item
    Composite structures subjected to underwater explosive loadings: a comprehensive review
    (Elsevier, 2021-05-01) Tran, P; Wu, CL; Saleh, M; Bortolan Neto, L; Nguyen-Xuan, H; Ferreira, AJM
    Composites materials and structures are increasingly used to replace conventional materials in civilian and defence-related maritime transportation and infrastructure such as naval vessels, submarines, civilian ships, and oil platforms for its better performance-to-weight ratio and electro-magnetic signature control. However, when subjected to under water explosions (UNDEX), navel composite structures experience highly nonlinear deformations and damages. Such transient deformation phenomena of composites and associated multiscale damages have been a subject of research for many years. This review aims to provide historical and methodological overviews of significant research and contributions in this area over the last 20 years from experimental programs, modelling approaches, post-mortem analysis techniques, analytical approximation and recently emerging area of data-led predictive simulations. UNDEX event is often described by a series of events including (a) the formation of the arriving shock wave, (b) the attenuation of the initial shock wave, (c) development of cavitation due to the reflected tension wave from free surface or the structural obstacles, (d) fluid-structure interaction-induced deformation and associated (e) cavitation coalescence and collapse. Such interconnected dynamic events and their influences on the behaviours of composite structures are subjected to extensive research and therefore summarised in this review work to highlight state-of-the-art field and laboratory-scaled experimental programs including investigations on low temperature and cavitation’s influences. Furthermore, the ongoing increase in the computing power and the development of advanced numerical methods have made it possible for multiscale and multi-physics simulations capturing the complex fluid dynamics associated with UNDEX. Over ten different modelling approaches, hydrocodes and their hybrid combination are summarised and discussed for potential applications. Review on current computational approaches also reveals the shortcomings of predictive modelling due to unavoidable simplifications, empirical assumptions on limited experimental data. Therefore, this work also provides a brief discussion on how data-led modelling approach such as artificial neural networks or deep learning, which is based largely on experimental data, could provide powerful assistance to analytical and deterministic numerical analysis. © 2021 Elsevier Ltd.
  • Thumbnail Image
    Item
    Experimental and numerical analysis of reinforced concrete subjected to blast
    (International Association of Protective Structures, 2020-11-23) Saleh, M; Remennikov, A; Antoinat, L; Bortolan Neto, L; Whittaker, A
    Dropped Loads and Accidental Blast in Nuclear Facilities Dropped loads (nuclear flasks) or accidental blast (combustible gases, deuterium/hydrogen release e.g. Fukushima accident) can undermine the structural integrity of containment structures and lead to a transient or sustained radiological release. Current regulatory guidelines and standards employ empirical formulas to calculate local responses of RC walls and slabs of nuclear facilities impacted by projectiles. These formulas were calibrated with data that are no longer available for reassessment and fail to predict complex scenarios. More accurate design equations can be developed by blast and impact analysis of RC panels using novel experimental and numerical techniques.
  • Thumbnail Image
    Item
    The Friedlander–Heaviside series for describing pressure-time history of reflected blast waves
    (Elsevier, 2023-01-20) Bortolan Neto, L
    The detonation of an explosive charge within a building or confined space will often result in reflected blast waves off the surrounding structure. Even though an extensive number of studies have examined this problem, only simplified mathematical descriptions of the pressure-time history are available. As these descriptions lack the fidelity required for detailed analysis of structural response to reflected blast loading, engineers and designers often must rely on expensive and resource intensive test data and validated numerical simulations to estimate dynamic structural loading. Other approaches which use pressure-impulse approximations provide reasonable predictions for estimating the global mechanical response of a structure, but they are unsuitable for evaluating localised structural failure. The Friedlander–Heaviside series is here introduced for describing the full dynamic overpressure-time history of reflected blast waves. This series provides a reasonably simple formulation that can describe with high accuracy the sequence of pressure peaks observed in pressure-time history curves from reflected blast waves. The Friedlander–Heaviside series is constructed by applying the superposition principle to a number of individual pulses formed by combining the well-known Friedlander equation with the Heaviside step function. Examples from the literature are used to validate the Friedlander–Heaviside series for describing pressure-time history of reflected blast waves. Once the required parameters have been established, the Friedlander–Heaviside series can then be readily applied in conjunction with advanced structural models for obtaining detailed evaluations of structural response to reflected blast loadings.
  • Thumbnail Image
    Item
    Numerical and analytical modelling of reinforced concrete subjected to large inertial impact
    (Australian Nuclear Science and Technology Organisation, 2018-12-11) Saleh, M; Bortolan Neto, L
    Dropped Loads in Nuclear Facilities Dropped loads can undermine the structural integrity of safety critical components. Relatively high impact velocities can result in significant local damage to the target, such as yielding of materials (bending), buckling or local failure or penetration. In nuclear facilities, a response of this sort may directly or indirectly lead to a transient or sustained radiological release.
  • Thumbnail Image
    Item
    On the prediction of creep behaviour of alloy 617 using Kachanov-Rabotnov model coupled with multi-objective genetic algorithm optimisation
    (Elsevier, 2022-10) Choi, J; Bortolan Neto, L; Wright, RN; Kruzic, JJ; Muránsky, O
    The accurate prediction of elevated-temperature creep behaviour of alloys is important for preventing catastrophic failure of systems operating under prolonged elevated temperature-stress conditions. Here, we couple the Kachanov-Rabotnov (K-R) creep model with a multi-objective genetic algorithm (MOGA) to predict the creep behaviour of Alloy 617 at 800°C, 900°C, and 1000°C, under various stress conditions. It is shown that the MOGA-optimised K-R creep model can capture the overall elevated-temperature behaviour of the alloy at 800°C under a wide range of stress conditions. However, at 900°C and 1000°C, oxidation leads to the atypical accumulation of creep plasticity, which the K-R model cannot account for. Nevertheless, it is shown that the proposed methodology of optimising the K-R model with a MOGA can consistently provide accurate results within the limits of the K-R model. Crown Copyright © 2022 Published by Elsevier Ltd.
  • Thumbnail Image
    Item
    Optimisation of numerical modelling for structures subjected to internal blast
    (International Symposium on Military Aspects of Blast and Shock (MABS), 2018-09-23) Saleh, M; Pickerd, V; Yiannakopoulos, G; Brincat, M; Bortolan Neto, L; Mathys, Z; Reid, W
    The design of modern military and naval platforms is often assisted by experiments and computational simulations, that provide relevant insights about material reliability, mechanical performance and design vulnerability to blast loading. An important design consideration for naval platforms is the damage response of structures from internal blast loading which is characterized by high strain rate loading and complex shock and blast wave interactions and reflections. To understand the damage response of structures under this loading condition, scaled experiments coupled with numerical simulations are used to identify (a) the temporal displacement fields using in-situ DIC measurements (b) onset of critical failure in various elements and (c) spatial distribution of internal pressure fields. A methodology for understanding the failure response of structures to internal blast loading is investigated using both scaled experiments and numerical modelling. Experimental data, including pressure, displacement, plastic strain and acceleration measurements, are compared with simulation results to determine modelling accuracy for both elastic and plastic deformation. The multi-scale modelling approach adopts a discretization technique for the structure by way of variations in the material property attributes of: weld material, Heat Affected Zone (HAZ) and parent material. The blast propagation and fluid structure interaction are achieved through an ALE simulation framework and provided insights into the deformation mechanisms exhibited in stiffened containers. Multiple structure configurations are simulated to explore this design space and results are compared with the experimentally observed loading and structural response behaviours. The simulation results, alongside the scaled experiments, provide a robust framework for the prediction of blast response of representative naval structures and allows for their optimization to improve both the subsystem and platform integrity.
  • Thumbnail Image
    Item
    Rapid mechanical evaluation of quadrangular steel plates subjected to localised blast loadings
    (Elsevier, 2020-03) Bortolan Neto, L; Saleh, M; Pickerd, V; Yiannakopoulos, G; Mathys, Z; Reid, W
    The design of modern military and naval platforms against weapon threats is often assisted by a combination of experimental, analytical and computational simulations. These tools provide relevant insights about material reliability, mechanical performance and platform design vulnerability to support the determination of safety critical aspects, such as response to blast and fragmentation loading. Analytical models are inherently simplified, limiting their ability to accurately model scenarios with complicated geometries and material properties, or highly non-linear loadings. Appropriate experimental and numerical modelling can overcome the limitations of analytical models but also require long lead times and high associated costs. These issues can be a point of concern for projects with strict development schedules, short time-to-solution, and limited resources. Machine learning techniques have proven viable in the development of fast-running models for highly non-linear problems. The present work explores four models based on the Multilayer Perceptron (MLP), a type of Artificial Neural Network (ANN), for assessing the mechanical response of mild steel plates subjected to localised blast loading. Experiments combined with validated Finite Element Analysis (FEA) models provide a hybrid dataset for training ANNs. The resultant dataset is a combination of sparsely populated experimental data with a denser dataset of validated FEA simulations. The final results demonstrate the potential of ANNs to incorporate high strain-rate material response behaviour, such as that from blast loading, into optimised models that can yield timely predictions of structural response. Crown Copyright © 2019 Published by Elsevier Ltd.
  • No Thumbnail Available
    Item
    Rapid vulnerability assessment of naval structures subjected to localised blast
    (Curran Associates, 2017-10-04) Bortolan Neto, L; Saleh, M; Pickerd, V; Yiannakopoulos, G; Mathys, Z; Reid, W
    The development of modern naval vessels is driven by the optimum balance between operational performance, technology restrictions and the costs of ownership. These factors impose limitations on all features of surface ships, including weaponry, structural materials, radar systems, and propulsors. Strategies must be set to identify design features and materials that can enhance the vessels protection in the event of shock loadings e.g. air blast and underwater explosions. Assessment of design solutions is a complicated task due to the large number of unknowns involved. Appropriate computational models and experimental tests can give insights into the expected mechanical behaviour to support the design process. The authors are developing a framework for vulnerability assessment, which includes experimental tests and appropriate finite element (FE) models of representative structural parts subjected to blast loading. This combined approach provides a comprehensive analysis tool but its complexity prevents the quick assessment of the vessel structural vulnerability when various design features and a range of materials are to be considered. To overcome this hurdle, a machine learning model based on Artificial Neural Networks is proposed to identify patterns in numerical and experimental data, yielding timely conclusions about the structural response. © 2017 The Royal Institution of Naval Architects