Abstract: The motivation of this work is to bridge the gap between experimental approaches in wind tunnel testing and numerical computations, in the field of structural design against strong winds. This paper focuses on the generation of an unsteady flow field, representative of a natural wind field, but still compatible with Computational Fluid Dynamics inlet requirements. A simple and “naive” procedure is explained, and the results are in good agreement with some international standards.
Abstract: The development of parallel Computational Fluid Dynamics (CFD) codes is a challenging task that entails efficient parallelization concepts and strategies in order to achieve good scalability values when running those codes on modern supercomputers with several thousands to millions of cores. In this paper, we present a hierarchical data structure for massive parallel computations that supports the coupling of a Navier–Stokes-based fluid flow code with the Boussinesq approximation in order to address complex thermal scenarios for energy-related assessments. The newly designed data structure is specifically designed with the idea of interactive data exploration and visualization during runtime of the simulation code; a major shortcoming of traditional high-performance computing (HPC) simulation codes. We further show and discuss speed-up values obtained on one of Germany’s top-ranked supercomputers with up to 140,000 processes and present simulation results for different engineering-based thermal problems.
Abstract: In this study we present a computational approach to the generation of the major geometric structures of an idealized murine lymph node (LN). In this generation, we consider the major compartments such as the subcapsular sinus, B cell follicles, trabecular and medullar sinuses, blood vessels and the T cell zone with a primary focus on the fibroblastic reticular cell (FRC) network. Confocal microscopy data of LN macroscopic structures and structural properties of the FRC network have been generated and utilized in the present model. The methodology sets a library of modules that can be used to assemble a solid geometric LN model and subsequently generate an adaptive mesh model capable of implementing transport phenomena. Overall, based on the use of high-resolution confocal microscopy and morphological analysis of cell 3D reconstructions, we have developed a computational model of the LN geometry, suitable for further investigation in studies of fluid transport and cell migration in this immunologically essential organ.
Abstract: Morphogenetic modelling and simulation help to understand the processes by which the form and shapes of organs (organogenesis) and organisms (embryogenesis) emerge. This requires two mutually coupled entities: the biomolecular signalling network and the tissue. Whereas the modelling of the signalling has been discussed and used in a multitude of works, the realistic modelling of the tissue has only started on a larger scale in the last decade. Here, common tissue modelling techniques are reviewed. Besides the continuum approach, the principles and main applications of the spheroid, vertex, Cellular Potts, Immersed Boundary and Subcellular Element models are discussed in detail. In recent years, many software frameworks, implementing the aforementioned methods, have been developed. The most widely used frameworks and modelling markup languages and standards are presented.
Abstract: There are numerous phylogenetic reconstruction methods and models available—but which should you use and why? Important considerations in phylogenetic analyses include data quality, structure, signal, alignment length and sampling. If poorly modelled, variation in rates of change across proteins and across lineages can lead to incorrect phylogeny reconstruction which can then lead to downstream misinterpretation of the underlying data. The risk of choosing and applying an inappropriate model can be reduced with some critical yet straightforward steps outlined in this paper. We use the question of the position of the root of placental mammals as our working example to illustrate the topological impact of model misspecification. Using this case study we focus on using models in a Bayesian framework and we outline the steps involved in identifying and assessing better fitting models for specific datasets.
Abstract: Computational and mathematical modeling is important in support of a better understanding of complex behavior in biology. For the investigation of biological systems, researchers have used computers to construct, verify, and validate models that describe the mechanisms behind biological processes in multi-scale representations. In this paper we combine Petri net models that represent the mycobacterial infection process and innate immune response at various levels of organization, from molecular interaction to granuloma dissemination. In addition to the conventional graphical representation of the Petri net, the outcome of the model is projected onto a 3D model representing the zebrafish embryo. In this manner we provide a visualization of the process in a simulation framework that portrays the infection in the living system.