Automatic visualization and control of arbitrary numerical simulations

Authors’ preprint version as submitted to ECCOMAS Congress 2016, Minisymposium 505 - Interactive Simulations in Computational Engineering. Abstract: Visualization of numerical simulation data has become a cornerstone for many industries and research areas today. There exists a large amount of software support, which is usually tied to specific problem domains or simulation platforms. However, numerical simulations have commonalities in the building blocks of their descriptions (e. g., dimensionality, range constraints, sample frequency). Instead of encoding these descriptions and their meaning into software architecures we propose to base their interpretation and evaluation on a data-centric model. This approach draws much inspiration from work of the IEEE Simulation Interoperability Standards Group as currently applied in distributed (military) training and simulation scenarios and seeks to extend those ideas. By using an extensible self-describing protocol format, simulation users as well as simulation-code providers would be able to express the meaning of their data even if no access to the underlying source code was available or if new and unforseen use cases emerge. A protocol definition will allow simulation-domain experts to describe constraints that can be used for automatically creating appropriate visualizations of simulation data and control interfaces. Potentially, this will enable leveraging innovations on both the simulation and visualization side of the problem continuum. We envision the design and development of algorithms and software tools for the automatic visualization of complex data from numerical simulations executed on a wide variety of platforms (e. g., remote HPC systems, local many-core or GPU-based systems). We also envisage using this automatically gathered information to control (or steer) the simulation while it is running, as well as providing the ability for fine-tuning representational aspects of the visualizations produced

Automatic visualization and control of arbitrary numerical simulations

Authors’ preprint version as submitted to ECCOMAS Congress 2016, Minisymposium 505 - Interactive Simulations in Computational Engineering. Abstract: Visualization of numerical simulation data has become a cornerstone for many industries and research areas today. There exists a large amount of software support, which is usually tied to specific problem domains or simulation platforms. However, numerical simulations have commonalities in the building blocks of their descriptions (e. g., dimensionality, range constraints, sample frequency). Instead of encoding these descriptions and their meaning into software architecures we propose to base their interpretation and evaluation on a data-centric model. This approach draws much inspiration from work of the IEEE Simulation Interoperability Standards Group as currently applied in distributed (military) training and simulation scenarios and seeks to extend those ideas. By using an extensible self-describing protocol format, simulation users as well as simulation-code providers would be able to express the meaning of their data even if no access to the underlying source code was available or if new and unforseen use cases emerge. A protocol definition will allow simulation-domain experts to describe constraints that can be used for automatically creating appropriate visualizations of simulation data and control interfaces. Potentially, this will enable leveraging innovations on both the simulation and visualization side of the problem continuum. We envision the design and development of algorithms and software tools for the automatic visualization of complex data from numerical simulations executed on a wide variety of platforms (e. g., remote HPC systems, local many-core or GPU-based systems). We also envisage using this automatically gathered information to control (or steer) the simulation while it is running, as well as providing the ability for fine-tuning representational aspects of the visualizations produced

Microgravity combustion science: A program overview

The promise of microgravity combustion research is introduced by way of a brief survey of results, the available set of reduced gravity facilities, and plans for experimental capabilities in the Space Station era. The study of fundamental combustion processes in a microgravity environment is a relatively new scientific endeavor. A few simple, precursor experiments were conducted in the early 1970's. Today the advent of the U.S. space shuttle and the anticipation of the Space Station Freedom provide for scientists and engineers a special opportunity, in the form of long duration microgravity laboratories, and need, in the form of spacecraft fire safety and a variety of terrestrial applications, to pursue fresh insight into the basic physics of combustion. The microgravity environment enables a new range of experiments to be performed since buoyancy-induced flows are nearly eliminated, normally obscured forces and flows may be isolated, gravitational settling or sedimentation is nearly eliminated, and larger time or length scales in experiments become permissible. The range of experiments completed to date was not broad, but is growing. Unexpected phenomena have been observed often in microgravity combustion experiments, raising questions about the degree of accuracy and completion of our classical understanding and our ability to estimate spacecraft fire hazards. Because of the field's relative immaturity, instrumentation has been restricted primarily to high-speed photography. To better explain these findings, more sophisticated diagnostic instrumentation, similar to that evolving in terrestrial laboratories, is being developed for use on Space Station Freedom and, along the way, in existing microgravity facilities

Agora : unified framework for crowd simulation research

Crowd simulation focuses on modeling the movements and behaviors of large groups of people. This area of study has become increasingly important because of its several applications in various fields such as urban planning, safety, and entertainment. In each of these domains, the presence of virtual agents exhibiting realistic behavior greatly enhances the quality of the simulations. However, the inherently multifaceted and intricate nature of human behavior presents a unique challenge, necessitating the effective combination of multiple behavior models. This thesis introduces a novel theoretical framework for modeling human behavior in crowd simulations, addressing the unresolved issue of combining a plethora of behavior models, often developed in isolation. The proposed framework decomposes human behavior into fundamental driving stimuli, which are then represented graphically through the heatmap paradigm. Subsequently, the agent behavior is influenced by the heatmaps, which guide them toward attractive areas and steer them away from repulsive locations based on the encoded stimuli. A key advantage of this approach lies in the ability to combine heatmaps using well-defined color operations, effectively integrating different aspects of human behavior. Furthermore, the heatmap paradigm facilitates objective comparison of simulation output with real-world data, employing image similarity metrics to evaluate model accuracy. To realize this framework, the thesis presents a modular software architecture designed to support various tasks involved in crowd simulation, emphasizing the separation of concerns for each task. This architecture comprises a collection of abstract modules, which are subsequently implemented using appropriate software components to realize the underlying features, resulting in the Agora framework. To assess the ability of Agora to support the various tasks involved in crowd simulation, two case studies are implemented and analyzed. The first case study simulates tourists visiting Þingvellir national park in Iceland, examining how their behavior is influenced by the visibility of the surrounding environment. The second case study employs Agora to model the thermal and density comfort levels of virtual pedestrians in an urban setting. The results demonstrate that Agora successfully supports the development, combination, and evaluation of crowd simulation models against real-world data. The authoring process, assisted by Agora, is significantly more streamlined compared to its native counterpart. The integration of multiple models is achieved by combining the heatmaps, resulting in plausible behavior, and the model assessment is made convenient through the evaluator within the framework. The thesis concludes by discussing the implications of these findings for the field of crowd simulation, highlighting the contributions and potential future directions of the Agora framework.Mannfjöldahermun fæst við gerð líkana af hreyfingu og hegðun stórra hópa af fólki. Mikilvægi þessa rannsóknasviðs hefur vaxið stöðugt vegna hagnýtingar á margvíslegum vetvangi, eins og til dæmis á vetvangi borgarskipulags, öryggis og afþreyingar. Þegar sýndarmenni hegða sér á sannfærandi hátt, leiðir það til betri hermunar fyrir þessi notkunarsvið. En mannleg hegðun er í eðli sínu margbrotin og flókin og því er það sérstök áskorun við smíði sýndarmenna að sameina, með áhrifaríkum hætti, mörg mismunandi hegðunarlíkön. Þessi ritgerð kynnir nýja fræðilega umgjörð líkanasmíði mannlegrar hegðunar fyrir mannfjöldahermun, sem tekur á þeim óleysta vanda að sameina fjölda hegðunarlíkana, sem oft eru þróuð með aðskildum hætti. Umgjörðin brýtur mannlega hegðun niður í grundvallar drifáreiti, sem eru sett fram grafískt útfrá hugmyndafræði hitakorta. Sýndarmennin hegða sér síðan undir áhrifum frá hitakortunum, sem vísa þeim í áttina að aðlaðandi svæðum og stýra þeim burt frá fráhrindandi svæðum, útfrá hinu umritaða áreiti. Lykilkostur þessarar nálgunar er sá eiginleiki að geta blandað saman hitakortum með vel skilgreindum litaaðgerðum, sem eru þá í raun samþætting mismunandi hliða mannlegrar hegðunar. Hitakortshugmyndafræðin auðveldar ennfremur hlutlægan samanburð hermunarúttaks og raungagna með notkun myndsamanburðarmælinga, til að meta nákvæmni líkana. Varðandi útfærslu, þá kynnir þessi ritgerð einingadrifna hugbúnaðarhögun sem er hönnuð til að styðja við ýmsa ferla mannfjöldahermunar, með áherslu á aðskilnað helstu viðfangsefna hvers ferlis. Þessi högun inniheldur safn huglægra eininga, sem síðan eru útfærðar með viðeigandi hugbúnaðarhlutum, sem raungera undirliggjandi eiginleika. Útkoman er sjálf Agora umbjörðin. Tvö sýnidæmi eru útfærð og greind til að meta getu Agoru til að styðja við ýmis mannfjöldahermunarverkefni. Fyrra dæmið hermir eftir ferðamönnum sem heimsækja Þingvallaþjóðgarð, og skoðar hvernig hegðun þeirra verður fyrir áhrifum sýnileika umhverfisins sem umleikur þá. Seinna dæmið nýtir Agoru til að smíða líkan af hitauppstreymis- og þéttleikaþægindum hjá sýndarvegfarendum í borgarumhverfi. Niðurstöðurnar sýna góðan árangur Agoru við að styðja þróun, samþættingu og mat mannfjöldahermunarlíkana gagnvart raungögnum. Þróunarferlið er verulega þjálla með Agoru en með hefðbundnum aðferðum. Samþætting margra líkana tókst með blöndun hitakorta, möguleg hegðun var framkölluð og mat á líkönunum varð þægilegra með umgjörðinni. Ritgerðinni lýkur með því að fjalla um áhrif þessara niðurstaðna á svið mannfjöldahegðunar, með áherslu á nýstálegt framlag þessarar rannsóknar og mögulega framtíðarþróun Agora umgjarðarinnar

Automatic visualization and control of arbitrary numerical simulations

Authors’ preprint version as submitted to ECCOMAS Congress 2016, Minisymposium 505 - Interactive Simulations in Computational Engineering. Abstract: Visualization of numerical simulation data has become a cornerstone for many industries and research areas today. There exists a large amount of software support, which is usually tied to specific problem domains or simulation platforms. However, numerical simulations have commonalities in the building blocks of their descriptions (e. g., dimensionality, range constraints, sample frequency). Instead of encoding these descriptions and their meaning into software architecures we propose to base their interpretation and evaluation on a data-centric model. This approach draws much inspiration from work of the IEEE Simulation Interoperability Standards Group as currently applied in distributed (military) training and simulation scenarios and seeks to extend those ideas. By using an extensible self-describing protocol format, simulation users as well as simulation-code providers would be able to express the meaning of their data even if no access to the underlying source code was available or if new and unforseen use cases emerge. A protocol definition will allow simulation-domain experts to describe constraints that can be used for automatically creating appropriate visualizations of simulation data and control interfaces. Potentially, this will enable leveraging innovations on both the simulation and visualization side of the problem continuum. We envision the design and development of algorithms and software tools for the automatic visualization of complex data from numerical simulations executed on a wide variety of platforms (e. g., remote HPC systems, local many-core or GPU-based systems). We also envisage using this automatically gathered information to control (or steer) the simulation while it is running, as well as providing the ability for fine-tuning representational aspects of the visualizations produced

The case of Ferbritas Cadastre Information System

The processes of mobilization of land for infrastructures of public and private domain are developed according to proper legal frameworks and systematically confronted with the impoverished national situation as regards the cadastral identification and regularization, which leads to big inefficiencies, sometimes with very negative impact to the overall effectiveness. This project report describes Ferbritas Cadastre Information System (FBSIC) project and tools, which in conjunction with other applications, allow managing the entire life-cycle of Land Acquisition and Cadastre, including support to field activities with the integration of information collected in the field, the development of multi-criteria analysis information, monitoring all information in the exploration stage, and the automated generation of outputs. The benefits are evident at the level of operational efficiency, including tools that enable process integration and standardization of procedures, facilitate analysis and quality control and maximize performance in the acquisition, maintenance and management of registration information and expropriation (expropriation projects). Therefore, the implemented system achieves levels of robustness, comprehensiveness, openness, scalability and reliability suitable for a structural platform. The resultant solution, FBSIC, is a fit-for-purpose cadastre information system rooted in the field of railway infrastructures. FBSIC integrating nature of allows: to accomplish present needs and scale to meet future services; to collect, maintain, manage and share all information in one common platform, and transform it into knowledge; to relate with other platforms; to increase accuracy and productivity of business processes related with land property management

Configuration of skilled tasks for execution in multipurpose and collaborative service robots

Several highly versatile mobile robots have been introduced during the last ten years. Some of these robots are working among people in exhibitions and other public places, such as museums and shopping centers. Unlike industrial robots, which are typically found only in manufacturing environments, service robots can be found in a variety of places, ranging from homes to offices, and from hospitals to restaurants. Developing mobile robots working co-operatively with humans raises not only interaction problems but problems in getting tasks accomplished. In an unstructured and dynamic environment this is not readily achievable because of the high degree of complexity of perception and motion of the robots. Such tasks require high-level perception and locomotion systems, not to mention control systems for all levels of task control. The lowest levels are controlling the motors and sensors of the robots and the highest are sophisticated task planners for complex and useful tasks. Human-friendly communication can be seen as an important factor in getting robots into our homes. In this work a new task configuration concept is proposed for multipurpose service robots. The concept gives guidelines for a software architecture and task managing system. Task configuration process presents a new method which makes it easier to configure a new task for a robot. The idea is the same as when a person tells another how a task should be performed. Novel method for executing tasks with service robots is also presented. Interpretive execution, keeping the focus on only one micro task at a time, makes it possible to modify plans during their execution. Multimodal interaction is important feature to provide collaboration between humans and robots. Multimodal interaction reduces the workload of the user by administering task configuration and execution. A novel solution for using multimodal human-robot interaction (HRI) as a part of the task description is presented. This thesis is a case study reporting the results when developing a task managing (from configuring to execution) platform for multipurpose service robots and studying its performance and use with several test cases. The platform that was developed has been implemented with the WorkPartner multipurpose service robot. The structure and operation of the platform have proved to be useful and several tasks have been carried out successfully

Seafloor characterization using airborne hyperspectral co-registration procedures independent from attitude and positioning sensors

The advance of remote-sensing technology and data-storage capabilities has progressed in the last decade to commercial multi-sensor data collection. There is a constant need to characterize, quantify and monitor the coastal areas for habitat research and coastal management. In this paper, we present work on seafloor characterization that uses hyperspectral imagery (HSI). The HSI data allows the operator to extend seafloor characterization from multibeam backscatter towards land and thus creates a seamless ocean-to-land characterization of the littoral zone