Subfilter-scale Stress Modelling for Large Eddy Simulations

A subfilter-scale (SFS) stress model is developed for large-eddy simulations (LES) and is tested on various benchmark problems in both wall-resolved and wall-modelled LES. The basic ingredients of the proposed model are the model length-scale, and the model parameter. The model length-scale is defined as a fraction of the integral scale of the flow, decoupled from the grid. The portion of the resolved scales (LES resolution) appears as a user-defined model parameter, an advantage that the user decides the LES resolution. The model parameter is determined based on a measure of LES resolution, the SFS activity. The user decides a value for the SFS activity (based on the affordable computational budget and expected accuracy), and the model parameter is calculated dynamically. Depending on how the SFS activity is enforced, two SFS models are proposed. In one approach the user assigns the global (volume averaged) contribution of SFS to the transport (global model), while in the second model (local model), SFS activity is decided locally (locally averaged). The models are tested on isotropic turbulence, channel flow, backward-facing step and separating boundary layer. In wall-resolved LES, both global and local models perform quite accurately. Due to their near-wall behaviour, they result in accurate prediction of the flow on coarse grids. The backward-facing step also highlights the advantage of decoupling the model length-scale from the mesh. Despite the sharply refined grid near the step, the proposed SFS models yield a smooth, while physically consistent filter-width distribution, which minimizes errors when grid discontinuity is present. Finally the model application is extended to wall-modelled LES and is tested on channel flow and separating boundary layer. Given the coarse resolution used in wall-modelled LES, near the wall most of the eddies become SFS and SFS activity is required to be locally increased. The results are in very good agreement with the data for the channel. Errors in the prediction of separation and reattachment are observed in the separated flow, that are somewhat improved with some modifications to the wall-layer model.

Modelling and simulations of ductile iron solidification-induced variations in mechanical behaviour on component and microstructural level

The mechanical behaviour and performance of a ductile iron component is highly dependent on the local variations in solidification conditions during the casting process. Here we show a framework which combine a previously developed closed chain of simulations for cast components with a micro-scale Finite Element Method (FEM) simulation of the behaviour and performance of the microstructure. A casting process simulation, including modelling of solidification and mechanical material characterization, provides the basis for a macro-scale FEM analysis of the component. A critical region is identified to which the micro-scale FEM simulation of a representative microstructure, generated using X-ray tomography, is applied. The mechanical behaviour of the different microstructural phases are determined using a surrogate model based optimisation routine and experimental data. It is discussed that the approach enables a link between solidification- and microstructure-models and simulations of as well component as microstructural behaviour, and can contribute with new understanding regarding the behaviour and performance of different microstructural phases and morphologies in industrial ductile iron components in service.

Understanding significant precipitation in Madeira island using high-resolution numerical simulations of real cases

In order to advance the knowledge about precipitation development over Madeira island, four rainfall patterns are investigated based on high-resolution numerical simulations performed with the MESO-NH model. The main environmental conditions during these precipitation periods are examined, and important factors leading to significant accumulated precipitation in Madeira are shown. We found that the combination of orographic effect and atmospheric conditions is essential for the establishment of each situation. Under a moist and conditionally unstable atmosphere, convection over the island is triggered, and its location was determined mainly by variations of the ambient flow, which was also associated with different moist Froude numbers. Interestingly, our results showed some similarities with situations discussed in idealized studies. However, the real variations of the atmospheric configuration confirm the complexity of significant precipitation development in mountainous regions. In addition, precipitating systems initially formed over the ocean were simulated reaching the island. The four periods were characterised by different time durations, and the local terrain interacting with the mesoscale circulation was decisive in producing a large part of the precipitation, which concentrated in distinct regions of the island induced by the airflow dynamic.

Numerical simulations of significant orographic precipitation in Madeira island

High-resolution simulations of high precipitation events with the MESO-NHmodel are presented, and also used to verify that increasing horizontal resolution in zones of complex orography, such as in Madeira island, improve the simulation of the spatial distribution and total precipitation. The simulations succeeded in reproducing the general structure of the cloudy systems over the ocean in the four periods considered of significant accumulated precipitation. The accumulated precipitation over theMadeirawas better represented with the 0.5 km horizontal resolution and occurred under four distinct synoptic situations. Different spatial patterns of the rainfall distribution over the Madeira have been identified

Numerical Simulations of Fog Events in Southern Portugal

This work aims at improving the knowledge on fog formation and its evolution in the Alentejo region (Portugal). For this purpose, brief regional fog climatology, essentially based on information from the Beja Air Base meteorological station, was produced and several numerical high resolution simulations were performed using the Meso-NH. The ECOCLIMAP database used to generate the model physiography was improved to include the Alqueva reservoir (~250 km2), filled in 2003. The model results were compared with surface and satellite observations, showing good agreement in terms of fog occurrence and persistence. Various forcing mechanisms for formation, development, and dissipation of fog were identified, confirming the influence of two small mountains that block the moist air from the Atlantic Ocean, preventing the fog from reaching innermost regions. The introduction of the Alqueva large reservoir induces changes in the landscape and environment. The effects of the water vapour addition and of the changes in mass and energy surface fluxes on fog formation and evolution were studied. It was found that the reservoir may have a direct impact on fog formation over the lake and its vicinity. Depending on the large scale meteorological conditions, their influence can be both positive and negative, in terms of spatial coverage and temporal persistence.

ISM simulations: an overview of models

Until recently the dynamical evolution of the interstellar medium (ISM) was simu- lated using collisional ionization equilibrium (CIE) conditions. However, the ISM is a dynamical system, in which the plasma is naturally driven out of equilibrium due to atomic and dynamic processes operating on different timescales. A step forward in the field comprises a multi-fluid approach taking into account the joint thermal and dynamical evolutions of the ISM gas.

Large Eddy Simulations applied to wind loading and pollutant dispersion

The application of Computational Fluid Dynamics based on the Reynolds-Averaged Navier-Stokes equations to the simulation of bluff body aerodynamics has been thoroughly investigated in the past. Although a satisfactory accuracy can be obtained for some urban physics problems their predictive capability is limited to the mean flow properties, while the ability to accurately predict turbulent fluctuations is recognized to be of fundamental importance when dealing with wind loading and pollution dispersion problems. The need to correctly take into account the flow dynamics when such problems are faced has led researchers to move towards scale-resolving turbulence models such as Large Eddy Simulations (LES). The development and assessment of LES as a tool for the analysis of these problems is nowadays an active research field and represents a demanding engineering challenge. This research work has two objectives. The first one is focused on wind loads assessment and aims to study the capabilities of LES in reproducing wind load effects in terms of internal forces on structural members. This differs from the majority of the existing research, where performance of LES is evaluated only in terms of surface pressures, and is done with a view of adopting LES as a complementary design tools alongside wind tunnel tests. The second objective is the study of LES capabilities in calculating pollutant dispersion in the built environment. The validation of LES in this field is considered to be of the utmost importance in order to conceive healthier and more sustainable cities. In order to validate the numerical setup adopted, a systematic comparison between numerical and experimental data is performed. The obtained results are intended to be used in the drafting of best practice guidelines for the application of LES in the urban physics field with a particular attention to wind load assessment and pollution dispersion problems.

Studying the alignment of 5-cyanobiphenyl on a polydimethylsiloxane surface through Molecular Dynamics simulations

For 40 years, at the University of Bologna, a group of researchers coordinated by professor Claudio Zannoni has been studying liquid crystals by employing computational techniques. They have developed effective models of these interesting, and still far from being completely understood, systems. They were able to reproduce with simulations important features of some liquid crystal molecules, such as transition temperature. Then they focused their attention on the interactions that these molecules have with different kinds of surface, and how these interactions affect the alignment of liquid crystals. The group studied the behaviour of liquid crystals in contact with different kinds of surfaces, from silica, either amorphous and crystalline, to organic self assembled monolayers (SAMs) and even some common polymers, such as polymethylmethacrylate (PMMA) and polystyrene (PS). Anyway, a library of typical surfaces is still far from being complete, and a lot of work must be done to investigate the cases which have not been analyzed yet. A hole that must be filled is represented by polydimethylsiloxane (PDMS), a polymer on which the interest of industry has enormously grown up in the last years, thanks to its peculiar features, allowing it to be employed in many fields of applications. It has been observed experimentally that PDMS causes 4-cyano-4’-pentylbiphenyl (well known as 5CB), one of the most common liquid crystal molecules, to align homeotropically (i.e. perpendicular) with respect to a surface made of this polymer. Even though some hypothesis have been presented to rationalize the effect, a clear explanation of this phenomenon has not been given yet. This dissertation shows the work I did during my internship in the group of professor Zannoni. The challenge that I had to tackle was to investigate, via Molecular Dynamics (MD) simulations, the reasons of 5CB homeotropic alignment on a PDMS surface, as the group had previously done for other surfaces.

Molecular simulations and modeling of pharmaceutically relevant RNA-processing enzymes

The two-metal-ion architecture is a structural feature found in a variety of RNA processing metalloenzymes or ribozymes (RNA-based enzymes), which control the biogenesis and the metabolism of vital RNAs, including non-coding RNAs (ncRNAs). Notably, such ncRNAs are emerging as key players for the regulation of cellular homeostasis, and their altered expression has been often linked to the development of severe human pathologies, from cancer to mental disorders. Accordingly, understanding the biological processing of ncRNAs is foundational for the development of novel therapeutic strategies and tools. Here, we use state-of the-art molecular simulations, complemented with X-ray crystallography and biochemical experiments, to characterize the RNA processing cycle as catalyzed by two two-metal-ion enzymes: the group II intron ribozymes and the RNase H1. We show that multiple and diverse cations are strategically recruited at and timely released from the enzymes’ active site during catalysis. Such a controlled cations’ trafficking leads to the recursive formation and disruption of an extended two-metal ion architecture that is functional for RNA-hydrolysis – from substrate recruitment to product release. Importantly, we found that these cations’ binding sites are conserved among other RNA-processing machineries, including the human spliceosome and CRISPR-Cas systems, suggesting that an evolutionarily-converged catalytic strategy is adopted by these enzymes to process RNA molecules. Thus, our findings corroborate and sensibly extend the current knowledge of two-metal-ion enzymes, and support the design of novel drugs targeting RNA-processing metalloenzymes or ribozymes as well as the rational engineering of novel programmable gene-therapy tools.

Models and Simulations of Diamond-like Carbon for large-area high voltage power diodes

Silicon-based discrete high-power devices need to be designed with optimal performance up to several thousand volts and amperes to reach power ratings ranging from few kWs to beyond the 1 GW mark. To this purpose, a key element is the improvement of the junction termination (JT) since it allows to drastically reduce surface electric field peaks which may lead to an earlier device failure. This thesis will be mostly focused on the negative bevel termination which from several years constitutes a standard processing step in bipolar production lines. A simple methodology to realize its counterpart, a planar JT with variation of the lateral doping concentration (VLD) will be also described. On the JT a thin layer of a semi insulating material is usually deposited, which acts as passivation layer reducing the interface defects and contributing to increase the device reliability. A thorough understanding of how the passivation layer properties affect the breakdown voltage and the leakage current of a fast-recovery diode is fundamental to preserve the ideal termination effect and provide a stable blocking capability. More recently, amorphous carbon, also called diamond-like carbon (DLC), has been used as a robust surface passivation material. By using a commercial TCAD tool, a detailed physical explanation of DLC electrostatic and transport properties has been provided. The proposed approach is able to predict the breakdown voltage and the leakage current of a negative beveled power diode passivated with DLC as confirmed by the successfully validation against the available experiments. In addition, the VLD JT proposed to overcome the limitation of the negative bevel architecture has been simulated showing a breakdown voltage very close to the ideal one with a much smaller area consumption. Finally, the effect of a low junction depth on the formation of current filaments has been analyzed by performing reverse-recovery simulations.

Advanced voxel-based CAD modelling for FSI simulations for automotive structures design

Additive Manufacturing (AM) is nowadays considered an important alternative to traditional manufacturing processes. AM technology shows several advantages in literature as design flexibility, and its use increases in automotive, aerospace and biomedical applications. As a systematic literature review suggests, AM is sometimes coupled with voxelization, mainly for representation and simulation purposes. Voxelization can be defined as a volumetric representation technique based on the model’s discretization with hexahedral elements, as occurs with pixels in the 2D image. Voxels are used to simplify geometric representation, store intricated details of the interior and speed-up geometric and algebraic manipulation. Compared to boundary representation used in common CAD software, voxel’s inherent advantages are magnified in specific applications such as lattice or topologically structures for visualization or simulation purposes. Those structures can only be manufactured with AM employment due to their complex topology. After an accurate review of the existent literature, this project aims to exploit the potential of the voxelization algorithm to develop optimized Design for Additive Manufacturing (DfAM) tools. The final aim is to manipulate and support mechanical simulations of lightweight and optimized structures that should be ready to be manufactured with AM with particular attention to automotive applications. A voxel-based methodology is developed for efficient structural simulation of lattice structures. Moreover, thanks to an optimized smoothing algorithm specific for voxel-based geometries, a topological optimized and voxelized structure can be transformed into a surface triangulated mesh file ready for the AM process. Moreover, a modified panel code is developed for simple CFD simulations using the voxels as a discretization unit to understand the fluid-dynamics performances of industrial components for preliminary aerodynamic performance evaluation. The developed design tools and methodologies perfectly fit the automotive industry’s needs to accelerate and increase the efficiency of the design workflow from the conceptual idea to the final product.

The role of the Rocky Mountains in shaping the atmospheric mean state and the response to tropical forcing in idealised simulations.

Understanding the natural and forced variability of the atmospheric general circulation and its drivers is one of the grand challenges in climate science. It is of paramount importance to understand to what extent the systematic error of climate models affects the processes driving such variability. This is done by performing a set of simulations (ROCK experiments) with an intermediate complexity atmospheric model (SPEEDY), in which the Rocky Mountains orography is increased or decreased to influence the structure of the North Pacific jet stream. For each of these modified-orography experiments, the climatic response to idealized sea surface temperature anomalies of varying intensity in the El Niño Southern Oscillation (ENSO) region is studied. ROCK experiments are characterized by variations in the Pacific jet stream intensity whose extension encompasses the spread of the systematic error found in Coupled Model Intercomparison Project (CMIP6) models. When forced with ENSO-like idealised anomalies, they exhibit a non-negligible sensitivity in the response pattern over the Pacific North American region, indicating that the model mean state can affect the model response to ENSO. It is found that the classical Rossby wave train response to ENSO is more meridionally oriented when the Pacific jet stream is weaker and more zonally oriented with a stronger jet. Rossby wave linear theory suggests that a stronger jet implies a stronger waveguide, which traps Rossby waves at a lower latitude, favouring a zonal propagation of Rossby waves. The shape of the dynamical response to ENSO affects the ENSO impacts on surface temperature and precipitation over Central and North America. A comparison of the SPEEDY results with CMIP6 models suggests a wider applicability of the results to more resources-demanding climate general circulation models (GCMs), opening up to future works focusing on the relationship between Pacific jet misrepresentation and response to external forcing in fully-fledged GCMs.

Hydrodynamic simulations of multiple stellar populations in globular clusters

The presence of multiple stellar populations in globular clusters (GCs) is now well accepted, however, very little is known regarding their origin. In this Thesis, I study how multiple populations formed and evolved by means of customized 3D numerical simulations, in light of the most recent data from spectroscopic and photometric observations of Local and high-redshift Universe. Numerical simulations are the perfect tool to interpret these data: hydrodynamic simulations are suited to study the early phases of GCs formation, to follow in great detail the gas behavior, while N-body codes permit tracing the stellar component. First, we study the formation of second-generation stars in a rotating massive GC. We assume that second-generation stars are formed out of asymptotic giant branch stars (AGBs) ejecta, diluted by external pristine gas. We find that, for low pristine gas density, stars mainly formed out of AGBs ejecta rotate faster than stars formed out of more diluted gas, in qualitative agreement with current observations. Then, assuming a similar setup, we explored whether Type Ia supernovae affect the second- generation star formation and their chemical composition. We show that the evolution depends on the density of the infalling gas, but, in general, an iron spread is developed, which may explain the spread observed in some massive GCs. Finally, we focused on the long-term evolution of a GC, composed of two populations and orbiting the Milky Way disk. We have derived that, for an extended first population and a low-mass second one, the cluster loses almost 98 percent of its initial first population mass and the GC mass can be as much as 20 times less after a Hubble time. Under these conditions, the derived fraction of second-population stars reproduces the observed value, which is one of the strongest constraints of GC mass loss.

Physical modeling and numerical simulations of degradation mechanisms in devices and insulators for power applications

In this thesis, a TCAD approach for the investigation of charge transport in amorphous silicon dioxide is presented for the first time. The proposed approach is used to investigate high-voltage silicon oxide thick TEOS capacitors embedded in the back-end inter-level dielectric layers for galvanic insulation applications. In the first part of this thesis, a detailed review of the main physical and chemical properties of silicon dioxide and the main physical models for the description of charge transport in insulators are presented. In the second part, the characterization of high-voltage MIM structures at different high-field stress conditions up to the breakdown is presented. The main physical mechanisms responsible of the observed results are then discussed in details. The third part is dedicated to the implementation of a TCAD approach capable of describing charge transport in silicon dioxide layers in order to gain insight into the microscopic physical mechanisms responsible of the leakage current in MIM structures. In particular, I investigated and modeled the role of charge injection at contacts and charge build-up due to trapping and de-trapping mechanisms in the oxide layer to the purpose of understanding its behavior under DC and AC stress conditions. In addition, oxide breakdown due to impact-ionization of carriers has been taken into account in order to have a complete representation of the oxide behavior at very high fields. Numerical simulations have been compared against experiments to quantitatively validate the proposed approach. In the last part of the thesis, the proposed approach has been applied to simulate the breakdown in realistic structures under different stress conditions. The TCAD tool has been used to carry out a detailed analysis of the most relevant physical quantities, in order to gain a detailed understanding on the main mechanisms responsible for breakdown and guide design optimization.

Numerical simulations of the spine for patient-specific models of severe scoliosis

In silico methods, such as musculoskeletal modelling, may aid the selection of the optimal surgical treatment for highly complex pathologies such as scoliosis. Many musculoskeletal models use a generic, simplified representation of the intervertebral joints, which are fundamental to the flexibility of the spine. Therefore, to model and simulate the spine, a suitable representation of the intervertebral joint is crucial. The aim of this PhD was to characterise specimen-specific models of the intervertebral joint for multi-body models from experimental datasets. First, the project investigated the characterisation of a specimen-specific lumped parameter model of the intervertebral joint from an experimental dataset of a four-vertebra lumbar spine segment. Specimen-specific stiffnesses were determined with an optimisation method. The sensitivity of the parameters to the joint pose was investigate. Results showed the stiffnesses and predicted motions were highly depended on both the joint pose. Following the first study, the method was reapplied to another dataset that included six complete lumbar spine segments under three different loading conditions. Specimen-specific uniform stiffnesses across joint levels and level-dependent stiffnesses were calculated by optimisation. Specimen-specific stiffness show high inter-specimen variability and were also specific to the loading condition. Level-dependent stiffnesses are necessary for accurate kinematic predictions and should be determined independently of one another. Secondly, a framework to create subject-specific musculoskeletal models of individuals with severe scoliosis was developed. This resulted in a robust codified pipeline for creating subject-specific, severely scoliotic spine models from CT data. In conclusion, this thesis showed that specimen-specific intervertebral joint stiffnesses were highly sensitive to joint pose definition and the importance of level-dependent optimisation. Further, an open-source codified pipeline to create patient-specific scoliotic spine models from CT data was released. These studies and this pipeline can facilitate the specimen-specific characterisation of the scoliotic intervertebral joint and its incorporation into scoliotic musculoskeletal spine models.