MS FT-2-2 7 Orthogonal polynomials and quadrature: Theory, computation, and applications

Quadrature rules find many applications in science and engineering. Their analysis is a classical area of applied mathematics and continues to attract considerable attention. This seminar brings together speakers with expertise in a large variety of quadrature rules. It is the aim of the seminar to provide an overview of recent developments in the analysis of quadrature rules. The computation of error estimates and novel applications also are described

Generalized averaged Gaussian quadrature and applications

A simple numerical method for constructing the optimal generalized averaged Gaussian quadrature formulas will be presented. These formulas exist in many cases in which real positive GaussKronrod formulas do not exist, and can be used as an adequate alternative in order to estimate the error of a Gaussian rule. We also investigate the conditions under which the optimal averaged Gaussian quadrature formulas and their truncated variants are internal

Computational nonlinear vibration analysis for distributed geometrical nonlinearities in structural dynamics

The demand to reduce the impact of aviation on the environment is leading jet engine manu- facturers to increase the fuel and propulsion efficiency of the engines. This in turn is pushing materials to their physical limits by undergoing increasingly higher thermo-mechanical loads. In this regime, blades and other engine components are subjected to large deforma- tions generating nonlinearities that activate new failure mechanisms not dealt with before. Therefore, vibration analysis is essential to develop new methodologies for the accurate prediction of components’ behaviour. This research focuses on investigating the effect of the distributed geometric nonlinearities and rotational speed on the dynamic behaviour of three-dimensional structures. The Green-Lagrange strain measures are employed in this research to express the nonlinear relationship between the displacement and the strain. The nonlinear algorithms used for the numerical simulations are developed based on the Finite Element Method combined with the Harmonic Balance method. The complex geometries are discretised by using the geometric exact three-dimensional solid elements. The forced response functions and the backbone curves for the steady-state response of the nonlinear system can be computed. The research aims to develop and validate methodologies for the identification and control of undesired vibration modes which will inform new design choices. Finite element modelling of the blades generally involves an immense number of degree-of-freedoms, which could be infeasible to compute. The reduced order modelling (ROM) techniques are crucial for achieving an accurate prediction of the nonlinear behaviour in an efficient way. Detailed computation strategies for the intrusive ROM methods are delivered. ROM techniques based on the linear and nonlinear mapping between the full model and the reduced basis are presented. The capabilities and limitations of both methods are assessed. The projection method based on the linear eigenmodes only has a slow converge to the full system. On the other hand, the quadratic manifold method with the static modal derivatives involved in the reduced coordinates provides a fast convergence.Open Acces

Theoretical Investigation of Static and Dynamic Properties of Zeolite ZSM-5 Based Amorphous Material

Results of molecular dynamics simulations on structural, vibrational and relaxational properties of zeolite ZSM-5 based amorphous solids are presented. The effects of extent of amorphization, measured by an energetic criterion, on properties like distribution of coordination numbers, internal surface area, ring statistics and effective pore size are studied. Ring statistics indicates that upon amorphization not only rings with larger size break down to give rings with smaller size, but that for intermediate degree of amorphization also larger rings are generated. The vibrational density of states was determined for different extents of amorphization. The vibrational modes are analyzed by projecting them on those of the SiO4 and Si-O-Si subunits and individual frequency-dependent contributions of stretching, bending and rotation are discussed. Analysis of low-frequency spectrum show that for higher crystallinity the intensity of the boson peak decreases upon amorphization, whereas the opposite behavior is observed for forms with lower crystallinity. These effects are explained in the framework of Maxwell counting of floppy modes. The modes associated with the boson peak for these materials are found to be mainly optic in nature. Relaxations were studied for temperatures below the critical temperature. At low temperatures the relaxations comprise mainly one-dimensional chains of atoms. The dimensionality of the relaxing centers increases with the temperature due to side branching. The possibility of having reversible jumps decreases with increasing temperature due to a strong drop in the potential energy during aging. There exist very prominent peaks in the van Hove correlation functions as a manifestation of the hopping processes. The dynamics of the oxygen atoms is found to be more heterogeneous than those of the silicon atoms. Ab initio many-body calculations on the strain energy ofW-silica, taken as a model system for edge-sharing tetrahedral SiO2-systems with respect to corner-sharing ones as in a-quartz was performed. Correlation contributions are found to play an important role to determine the stability of edge-sharing units. Our calculation reveal that edge-sharing SiO4 tetrahedra in (partially) amorphous silicate systems are possible at a modest energetic expense

Model-Driven Software Engineering for Computational Science Applied to a Marine Ecosystem Model

The ever-increasing complexity of in silico experiments in computational science is reflected in the growing complexity of the simulation software enabling these experiments. However, computational scientists rarely employ state-of-the-art software engineering methods, which negatively affects their productivity as well as the reliability of their scientific results. To tackle this challenge, this book introduces the Sprat Approach, which hierarchically integrates multiple domain-specific languages to facilitate the cooperation of scientists from different disciplines and to support them in creating well-engineered software without extensive software engineering training. To evaluate the Sprat Approach, it is applied to the implementation of the Sprat Marine Ecosystem Model in an exploratory case study. The Sprat Marine Ecosystem Model is a novel end-to-end ecosystem model based on population balance equations. In order to evaluate the Sprat Model, it is parametrized for the eastern Scotian Shelf ecosystem with its intertwined direct and indirect fish stock interactions, which previously could not be modeled satisfactorily. The simulation results described in this book provide new insights into the main drivers of regime shifts in marine ecosystems

Real-Time Quantum Noise Suppression In Very Low-Dose Fluoroscopy

Fluoroscopy provides real-time X-ray screening of patient's organs and of various radiopaque objects, which make it an invaluable tool for many interventional procedures. For this reason, the number of fluoroscopy screenings has experienced a consistent growth in the last decades. However, this trend has raised many concerns about the increase in X-ray exposure, as even low-dose procedures turned out to be not as safe as they were considered, thus demanding a rigorous monitoring of the X-ray dose delivered to the patients and to the exposed medical staff. In this context, the use of very low-dose protocols would be extremely beneficial. Nonetheless, this would result in very noisy images, which need to be suitably denoised in real-time to support interventional procedures. Simple smoothing filters tend to produce blurring effects that undermines the visibility of object boundaries, which is essential for the human eye to understand the imaged scene. Therefore, some denoising strategies embed noise statistics-based criteria to improve their denoising performances. This dissertation focuses on the Noise Variance Conditioned Average (NVCA) algorithm, which takes advantage of the a priori knowledge of quantum noise statistics to perform noise reduction while preserving the edges and has already outperformed many state-of-the-art methods in the denoising of images corrupted by quantum noise, while also being suitable for real-time hardware implementation. Different issues are addressed that currently limit the actual use of very low-dose protocols in clinical practice, e.g. the evaluation of actual performances of denoising algorithms in very low-dose conditions, the optimization of tuning parameters to obtain the best denoising performances, the design of an index to properly measure the quality of X-ray images, and the assessment of an a priori noise characterization approach to account for time-varying noise statistics due to changes of X-ray tube settings. An improved NVCA algorithm is also presented, along with its real-time hardware implementation on a Field Programmable Gate Array (FPGA). The novel algorithm provides more efficient noise reduction performances also for low-contrast moving objects, thus relaxing the trade-off between noise reduction and edge preservation, while providing a further reduction of hardware complexity, which allows for low usage of logic resources also on small FPGA platforms. The results presented in this dissertation provide the means for future studies aimed at embedding the NVCA algorithm in commercial fluoroscopic devices to accomplish real-time denoising of very low-dose X-ray images, which would foster their actual use in clinical practice

On connectivity in the central nervous systeem : a magnetic resonance imaging study

Brain function has long been the realm of philosophy, psychology and psychiatry and since the mid 1800s, of histopathology. Through the advent of magnetic imaging in the end of the last century, an in vivo visualization of the human brain became available. This thesis describes the development of two unique techniques, imaging of diffusion of water protons and manganese enhanced imaging, that both allow for the depiction of white matter tracts. The reported studies show, that these techniques can be used for a three-dimensional depiction of fiber bundles and that quantitative measures reflecting fiber integrity and neuronal function can be extracted from such data. In clinical applications, the potential use of the developed methods is illustrated in human gliomas, as measure for fiber infiltration, and in spinal cord injury, to monitor potential neuroprotective and __regenerative medication.UBL - phd migration 201

Fuelling the zero-emissions road freight of the future: routing of mobile fuellers

The future of zero-emissions road freight is closely tied to the sufficient availability of new and clean fuel options such as electricity and Hydrogen. In goods distribution using Electric Commercial Vehicles (ECVs) and Hydrogen Fuel Cell Vehicles (HFCVs) a major challenge in the transition period would pertain to their limited autonomy and scarce and unevenly distributed refuelling stations. One viable solution to facilitate and speed up the adoption of ECVs/HFCVs by logistics, however, is to get the fuel to the point where it is needed (instead of diverting the route of delivery vehicles to refuelling stations) using "Mobile Fuellers (MFs)". These are mobile battery swapping/recharging vans or mobile Hydrogen fuellers that can travel to a running ECV/HFCV to provide the fuel they require to complete their delivery routes at a rendezvous time and space. In this presentation, new vehicle routing models will be presented for a third party company that provides MF services. In the proposed problem variant, the MF provider company receives routing plans of multiple customer companies and has to design routes for a fleet of capacitated MFs that have to synchronise their routes with the running vehicles to deliver the required amount of fuel on-the-fly. This presentation will discuss and compare several mathematical models based on different business models and collaborative logistics scenarios