Cactus is an open source problem solving environment designed for scientists and engineers. Its m... more Cactus is an open source problem solving environment designed for scientists and engineers. Its modular structure facilitates parallel computation across different architectures and collaborative code development between different groups. The Cactus Code originated in the academic research community, where it has been developed and used over many years by a large international collaboration of physicists and computational scientists. We discuss
... Edwin Mathews1, Werner Benger1, Marcel Ritter2 1Center for Computation & Technology at Lo... more ... Edwin Mathews1, Werner Benger1, Marcel Ritter2 1Center for Computation & Technology at Louisiana State University (CCT/LSU), Baton Rouge, Louisiana, USA 2 Unit of Hydraulic Engineering ... S = 1 detI ( IIxxIyy − IIxyIxy IIxyIyy − IIyyIxy IIxyIxx − IIxxIxy IIyyIxx − IIxyIxy ) ...
PFG – Journal of Photogrammetry, Remote Sensing and Geoinformation Science, 2021
Topo-bathymetric LiDAR data captured with modern systems are complex. The primary information rec... more Topo-bathymetric LiDAR data captured with modern systems are complex. The primary information received is a time-dependent amplitude variation of the reflected light. These so-called waveforms are processed into singular points with 3D coordinates by advanced on-board devices of the LiDAR sensor (online waveform processing), but the full-waveform (FWF) information may be available as well. However, available software tools are often insufficient to manage all required processing steps. Common file formats do not allow to store originally recorded sensor parameters together with subsequently processed parameters in one database or file. The FWF, however, can contain information to better cover the terrain below dense vegetation, and to improve aerial coverage of the water ground. Thus, we extended the software suite HydroVISH with respect to an integrated FWF processing pipeline. Employing the open-source Hierarchical Data Format V5 (HDF5) with the F5 layout thereby allows for efficient data storage and handling throughout the processing chain. The potential benefit of performing a comprehensive FWF analysis can be assessed via the simultaneous visualization of the complete FWF information on all points in an interactive display environment. Next, the valuable point information is extracted using various provided FWF processing tools, such as Richardson–Lucy deconvolution or Gaussian decomposition. For topo-bathymetric data, the correct point classification of the terrain above and below water as well as the actual water surface is crucial to correctly calculate the refraction correction for points beneath the water surface. Finally, we also outline the implemented classification approach for the terrain and water surface. Integrierte Full-Waveform Analyse und Klassifizierungsansätze für topo-bathymetrische Datenverarbeitung und Visualisierung in HydroVISH . Topo-bathymetrische LiDAR-Daten, wie sie mit modernen Sensoren gewonnen werden, sind komplex. Die vom Sensor empfangene Primärinformation ist dabei eine zeitabhängige Variation der Signalamplitude des reflektierten Lichts. Diese sogenannten Wellenformen (Full-Waveform, FWF) werden mittels On-Board-Komponenten des jeweiligen LiDAR-Systems zu einzelnen Punkten mit 3D-Koordinaten verarbeitet (Online-Waveform Processing), aber auch als Bestandteil der Rohdaten abgespeichert. Mit verfügbaren Software-Lösungen können oftmals nicht alle erforderlichen Schritte im Rahmen der Datenprozessierung abgebildet werden. Zudem können mit gebräuchlichen Dateiformaten nicht alle bei der Datenerhebung ursprünglich aufgezeichneten Parameter zusammen mit nachfolgend berechneten Parametern in einer Datenbank oder einer Datei gespeichert werden. Die FWF kann jedoch wertvolle Informationen enthalten, mit denen sich der Geländeverlauf unter Wasser und unterhalb dichter Vegetation wesentlich besser erfassen lässt und damit eine verbesserte räumliche Abdeckung des Geländes ermöglicht. Wir haben daher das Softwarepaket HydroVISH um eine substantielle FWF-Prozessierungskette erweitert. Die Verwendung des quelloffenen Hierarchical Data Format V5 (HDF5) im F5-Layout ermöglicht dabei eine effiziente Datenspeicherung und -handhabung über die gesamte Prozesskette hinweg. Der potenzielle Mehrwert einer umfassenden FWF-Analyse kann durch die simultane Darstellung aller FWF-Verläufe und Laserpunkte in einer interaktiven Visualisierungsumgebung am besten evaluiert werden. Daran anschließend werden mit Hilfe verschiedener FWF-Verarbeitungswerkzeuge (z.B. Entfaltung nach Richardson-Lucy oder Gauss'sche Zerlegung) die nützlichen Punktinformationen aus der FWF abgeleitet. Für topo-bathymetrische Daten ist die exakte Klassifizierung sowohl von Geländepunkten über und unter Wasser als auch der Wasseroberfläche entscheidend für die korrekte Berechnung der Refraktion bzgl. aller unter Wasser liegenden Punkte. Daher beschreiben wir abschließend den in HydroVISH implementierten Ansatz zur Klassifizierung des Geländes und der Wasseroberfläche.
Scientific visualisation of computational or observational data sets in material sciences is esse... more Scientific visualisation of computational or observational data sets in material sciences is essential for studying data sets of ever increasing complexity. Rather than just using and implementing self-contained solutions to address particular problems, a systematic approach for modelling data sets opens the gateway to sharing data sets with other applications and general purpose visualisation frameworks. The fibre bundle data model is a mathematical description encompassing many diverse data types, ranging from molecular dynamics via continuum mechanics describing solid and fluids to finite elements. It fits well to be mapped to the Hierarchical Data Format file format as a widely used data storage container. Still various choices remain on such a data mapping and are reviewed in this article. The fibre bundle data model provides a classification scheme for data sets on an abstract level, disregarding implementation details and therefore eases selecting visualisation methods appropriate for the underlying data. Data are hereby studied via properties of their so called base space and fibre space. The base space is describing properties of the numerical discretion scheme, the fibre space is describing physical quantities. Visual data analysis of both spaces is important, but can be considered widely independent, depending on the need to either study computational or physical aspects of the data. Methods to study the topological structure of the base space complement methods to study scalar, vector and tensor fields and provide a highly systematic approach for scientific visualisation in material sciences.
Proceedings of SPIE - The International Society for Optical Engineering
A new general-purpose technique for the visualization of time-dependent Symmetric positive defini... more A new general-purpose technique for the visualization of time-dependent Symmetric positive definite tensor fields of rank two is described. It is based on a splatting technique that is built from tiny transparent glyph primitives which are capable of incorporating the full directional information content of a tensor. The result is an information-rich image that allows to read off the preferred directions in a tensor field. It is useful for analyzing slices or volumes of a three-dimensional tensor field and can be overlayed with standard volume rendering or color mapping. The application of the rendering technique is demonstrated on numerically simulated general relativistic data and a measured diffusion tensor field of a human brain.
The Tenth Marcel Grossmann Meeting, On Recent Developments in Theoretical and Experimental General Relativity, Gravitation and Relativistic Field Theories - Proceedings of the MG10 Meeting, 2006
Cactus is an open source problem solving environment designed for scientists and engineers. Its m... more Cactus is an open source problem solving environment designed for scientists and engineers. Its modular structure facilitates parallel computation across different architectures and collaborative code development between different groups. The Cactus Code originated in the academic research community, where it has been developed and used over many years by a large international collaboration of physicists and computational scientists. We discuss
... Edwin Mathews1, Werner Benger1, Marcel Ritter2 1Center for Computation & Technology at Lo... more ... Edwin Mathews1, Werner Benger1, Marcel Ritter2 1Center for Computation & Technology at Louisiana State University (CCT/LSU), Baton Rouge, Louisiana, USA 2 Unit of Hydraulic Engineering ... S = 1 detI ( IIxxIyy − IIxyIxy IIxyIyy − IIyyIxy IIxyIxx − IIxxIxy IIyyIxx − IIxyIxy ) ...
PFG – Journal of Photogrammetry, Remote Sensing and Geoinformation Science, 2021
Topo-bathymetric LiDAR data captured with modern systems are complex. The primary information rec... more Topo-bathymetric LiDAR data captured with modern systems are complex. The primary information received is a time-dependent amplitude variation of the reflected light. These so-called waveforms are processed into singular points with 3D coordinates by advanced on-board devices of the LiDAR sensor (online waveform processing), but the full-waveform (FWF) information may be available as well. However, available software tools are often insufficient to manage all required processing steps. Common file formats do not allow to store originally recorded sensor parameters together with subsequently processed parameters in one database or file. The FWF, however, can contain information to better cover the terrain below dense vegetation, and to improve aerial coverage of the water ground. Thus, we extended the software suite HydroVISH with respect to an integrated FWF processing pipeline. Employing the open-source Hierarchical Data Format V5 (HDF5) with the F5 layout thereby allows for efficient data storage and handling throughout the processing chain. The potential benefit of performing a comprehensive FWF analysis can be assessed via the simultaneous visualization of the complete FWF information on all points in an interactive display environment. Next, the valuable point information is extracted using various provided FWF processing tools, such as Richardson–Lucy deconvolution or Gaussian decomposition. For topo-bathymetric data, the correct point classification of the terrain above and below water as well as the actual water surface is crucial to correctly calculate the refraction correction for points beneath the water surface. Finally, we also outline the implemented classification approach for the terrain and water surface. Integrierte Full-Waveform Analyse und Klassifizierungsansätze für topo-bathymetrische Datenverarbeitung und Visualisierung in HydroVISH . Topo-bathymetrische LiDAR-Daten, wie sie mit modernen Sensoren gewonnen werden, sind komplex. Die vom Sensor empfangene Primärinformation ist dabei eine zeitabhängige Variation der Signalamplitude des reflektierten Lichts. Diese sogenannten Wellenformen (Full-Waveform, FWF) werden mittels On-Board-Komponenten des jeweiligen LiDAR-Systems zu einzelnen Punkten mit 3D-Koordinaten verarbeitet (Online-Waveform Processing), aber auch als Bestandteil der Rohdaten abgespeichert. Mit verfügbaren Software-Lösungen können oftmals nicht alle erforderlichen Schritte im Rahmen der Datenprozessierung abgebildet werden. Zudem können mit gebräuchlichen Dateiformaten nicht alle bei der Datenerhebung ursprünglich aufgezeichneten Parameter zusammen mit nachfolgend berechneten Parametern in einer Datenbank oder einer Datei gespeichert werden. Die FWF kann jedoch wertvolle Informationen enthalten, mit denen sich der Geländeverlauf unter Wasser und unterhalb dichter Vegetation wesentlich besser erfassen lässt und damit eine verbesserte räumliche Abdeckung des Geländes ermöglicht. Wir haben daher das Softwarepaket HydroVISH um eine substantielle FWF-Prozessierungskette erweitert. Die Verwendung des quelloffenen Hierarchical Data Format V5 (HDF5) im F5-Layout ermöglicht dabei eine effiziente Datenspeicherung und -handhabung über die gesamte Prozesskette hinweg. Der potenzielle Mehrwert einer umfassenden FWF-Analyse kann durch die simultane Darstellung aller FWF-Verläufe und Laserpunkte in einer interaktiven Visualisierungsumgebung am besten evaluiert werden. Daran anschließend werden mit Hilfe verschiedener FWF-Verarbeitungswerkzeuge (z.B. Entfaltung nach Richardson-Lucy oder Gauss'sche Zerlegung) die nützlichen Punktinformationen aus der FWF abgeleitet. Für topo-bathymetrische Daten ist die exakte Klassifizierung sowohl von Geländepunkten über und unter Wasser als auch der Wasseroberfläche entscheidend für die korrekte Berechnung der Refraktion bzgl. aller unter Wasser liegenden Punkte. Daher beschreiben wir abschließend den in HydroVISH implementierten Ansatz zur Klassifizierung des Geländes und der Wasseroberfläche.
Scientific visualisation of computational or observational data sets in material sciences is esse... more Scientific visualisation of computational or observational data sets in material sciences is essential for studying data sets of ever increasing complexity. Rather than just using and implementing self-contained solutions to address particular problems, a systematic approach for modelling data sets opens the gateway to sharing data sets with other applications and general purpose visualisation frameworks. The fibre bundle data model is a mathematical description encompassing many diverse data types, ranging from molecular dynamics via continuum mechanics describing solid and fluids to finite elements. It fits well to be mapped to the Hierarchical Data Format file format as a widely used data storage container. Still various choices remain on such a data mapping and are reviewed in this article. The fibre bundle data model provides a classification scheme for data sets on an abstract level, disregarding implementation details and therefore eases selecting visualisation methods appropriate for the underlying data. Data are hereby studied via properties of their so called base space and fibre space. The base space is describing properties of the numerical discretion scheme, the fibre space is describing physical quantities. Visual data analysis of both spaces is important, but can be considered widely independent, depending on the need to either study computational or physical aspects of the data. Methods to study the topological structure of the base space complement methods to study scalar, vector and tensor fields and provide a highly systematic approach for scientific visualisation in material sciences.
Proceedings of SPIE - The International Society for Optical Engineering
A new general-purpose technique for the visualization of time-dependent Symmetric positive defini... more A new general-purpose technique for the visualization of time-dependent Symmetric positive definite tensor fields of rank two is described. It is based on a splatting technique that is built from tiny transparent glyph primitives which are capable of incorporating the full directional information content of a tensor. The result is an information-rich image that allows to read off the preferred directions in a tensor field. It is useful for analyzing slices or volumes of a three-dimensional tensor field and can be overlayed with standard volume rendering or color mapping. The application of the rendering technique is demonstrated on numerically simulated general relativistic data and a measured diffusion tensor field of a human brain.
The Tenth Marcel Grossmann Meeting, On Recent Developments in Theoretical and Experimental General Relativity, Gravitation and Relativistic Field Theories - Proceedings of the MG10 Meeting, 2006
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