Fluka Raytracer

The project described in this document was developed as the work for a technical student position at CERN in Geneva, Switzerland. CERN is the European Organization for Nuclear Research and is one of the leading physics laboratories across the world. The development of the current project was held by the section EN-STI-EET (Engineering; Sources Targets and Interactions; Emerging Energy Technologies), which in collaboration with INFN Institute, Italy is in charge of developing and maintaining the Monte Carlo generator FLUKA . FLUKA is a general purpose tool for calculations of particle transport and interactions with matter, covering an extended range of applications spanning from proton and electron accelerator shielding to target design, calorimetry, activation, dosimetry, detector design, Accelerator Driven Systems, cosmic rays, neutrino physics, radiotherapy etc.Siñuela Pastor, D. (2013). Fluka Raytracer. http://hdl.handle.net/10251/27328.Archivo delegad

Advances in Sonar Technology

The demand to explore the largest and also one of the richest parts of our planet, the advances in signal processing promoted by an exponential growth in computation power and a thorough study of sound propagation in the underwater realm, have lead to remarkable advances in sonar technology in the last years.The work on hand is a sum of knowledge of several authors who contributed in various aspects of sonar technology. This book intends to give a broad overview of the advances in sonar technology of the last years that resulted from the research effort of the authors in both sonar systems and their applications. It is intended for scientist and engineers from a variety of backgrounds and even those that never had contact with sonar technology before will find an easy introduction with the topics and principles exposed here

Cloudy with a chance of starlight : coupling of smoothed particle hydrodynamics and Monte Carlo radiative transfer for the study of ionising stellar feedback

Ionising radiation is present in a variety of astrophysical problems, and it is particularly important for shaping the process of star formation in molecular clouds, containing hot, high-mass stars. In order to account for the effects of ionising radiation within numerical models of star formation, we need to combine a hydrodynamics method with a radiative transfer method and obtain a radiation hydrodynamics scheme (RHD). In this thesis I achieve live radiation hydrodynamics by coupling the Smoothed Particle Hydrodynamics (SPH) code Phantom with the Monte Carlo Radiative Transfer (MCRT) code CMacIonize. Since SPH is particle-based and MCRT is grid-based, I construct an unstructured, Voronoi grid in order to establish a link between the two codes. In areas with large density gradients, a Voronoi grid based purely on the SPH particle positions achieves insufficient resolution, and therefore I propose a novel algorithm for inserting a small number of additional grid cells to improve the local resolution. Furthermore, the MCRT calculations require the knowledge of an average density for each Voronoi cell. To address this, I develop an analytic density mapping from SPH to a Voronoi grid, by deriving an expression for the integrals of a series of kernel functions over the volume of a random polyhedron. Finally, I demonstrate the validity of the live RHD through the benchmark test of D-type expansion of an H II region, where good agreement is shown with the existing literature. The RHD implementation is then used to perform a proof-of-concept simulation of a collapsing cloud, which produces high-mass stars and is subsequently partially ionised by them. The presented code is a valuable tool for future star formation studies, and it can be used for modelling a broad range of additional astronomical problems involving ionising radiation and hydrodynamics."This thesis received funding from the European Research Council for the FP7 ERC advanced grant project ECOGAL. The presented work used the DiRAC Complexity system, operated by the University of Leicester IT Services, which forms part of the STFC DiRAC HPC Facility (www.dirac.ac.uk). This equipment is funded by BIS National E-Infrastructure capital grant ST/K000373/1 and STFC DiRAC Operations grant ST/K0003259/1. DiRAC is part of the National E-Infrastructure." -- Acknowledgement

Intuitive visualization of surface properties of biomolecules

In living cells, proteins are in continuous motion and interaction with the surrounding medium and/or other proteins and ligands. These interactions are mediated by protein features such as Electrostatic Potential (EP) and hydropathy expressed as Molecular Lipophilic Potential (MLP). The availability of protein structures enables the study of their surfaces and surface characteristics, based on atomic contribution. Traditionally, these properties are calculated by phisicochemical programs and visualized as range of colours that vary according to the tool used and imposes the necessity of a legend to decrypt it. The use of colour to encode both characteristics makes the simultaneous visualization almost impossible. This is why most of the times EP and MLP are presented in two different images. In this thesis, we describe a novel and intuitive code for the simultaneous visualization of these properties. For our purpose we use Blender, an open-source, free, cross-platform 3D application used for modelling, animation, gaming and rendering. On the basis of Blender, we developed BioBlender, a package dedicated to biological work: elaboration of proteins motion with the simultaneous visualization of their chemical and physical features. Blender's Game Engine, equipped with specific physico-chemical rules is used to elaborate the motion of proteins, interpolating between different conformations (NMR collections or different X-rays of the same protein). We obtain a physically plausible sequence of intermediate conformations which are the basis for the subsequent visual elaboration. A new visual code is introduced for MLP visualization: a range of optical features that goes from dull-rough surfaces for the most hydrophilic areas to shiny-smooth surfaces for the most lipophilic ones. This kind of representation permits a photorealistic rendering of the smooth spatial distribution of the values of MLP on the surface of the protein. EP is represented as animated line particles that flow along field lines, from positive to negative, proportional to the total charge of the protein. Our system permits EP and MLP simultaneous visualization of molecules and, in the case of moving proteins, the continuous perception of these features, calculated for each intermediate conformation. Moreover, this representation contributes to gain insight into the molecules function by drawing viewer's attention to the most active regions of the protein

Applied Metaheuristic Computing

For decades, Applied Metaheuristic Computing (AMC) has been a prevailing optimization technique for tackling perplexing engineering and business problems, such as scheduling, routing, ordering, bin packing, assignment, facility layout planning, among others. This is partly because the classic exact methods are constrained with prior assumptions, and partly due to the heuristics being problem-dependent and lacking generalization. AMC, on the contrary, guides the course of low-level heuristics to search beyond the local optimality, which impairs the capability of traditional computation methods. This topic series has collected quality papers proposing cutting-edge methodology and innovative applications which drive the advances of AMC