Services to support simulation workflows for next generation aircraft structures
In the intricate and rapidly advancing domain of aerospace engineering, the task of designing and manufacturing next-generation aircraft structures stands as a monumental challenge. The aerospace industry, with its relentless pursuit of innovation and efficiency, is constantly pushing the boundaries...
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| Formato: | tesis de maestría |
| Fecha de publicación: | 2023 |
| País: | España |
| Recursos: | Universitat Politècnica de Catalunya (UPC) |
| Repositorio: | UPCommons. Portal del coneixement obert de la UPC |
| Idioma: | inglés |
| OAI Identifier: | oai:upcommons.upc.edu:2117/402319 |
| Acesso em linha: | https://hdl.handle.net/2117/402319 |
| Access Level: | acceso abierto |
| Palavra-chave: | High performance computing Aerospace engineering PyCOMPSs dynamic workflows HPC simulations sensitivity analysis Montecarlo simulations CAELESTIS service Càlcul intensiu (Informàtica) Enginyeria aeroespacial Àrees temàtiques de la UPC::Informàtica::Arquitectura de computadors |
| Resumo: | In the intricate and rapidly advancing domain of aerospace engineering, the task of designing and manufacturing next-generation aircraft structures stands as a monumental challenge. The aerospace industry, with its relentless pursuit of innovation and efficiency, is constantly pushing the boundaries of what’s possible. As this industry propels forward, it becomes imperative to harness the power of high-performance computing (HPC) to drive these innovations. HPC, with its unparalleled computational capabilities, offers the potential to simulate complex sce- narios, model intricate structures, and predict outcomes with high precision. This is where the CAELESTIS project plays a pivotal role. The CAELESTIS project, a beacon of advancement in the aerospace sector, recognizes the transformative potential of HPC. By integrating HPC into the aerospace design process, simu- lation, when executed on HPC platforms, can drastically reduce the time and resources tradi- tionally required. This enables engineers to test and iterate designs with unprecedented speed and accuracy, ensuring that the aircrafts of tomorrow are not only cutting-edge but also safe and efficient. Central to this thesis is the exploration and development of a service to generate dynamic simulation workflows. These workflows, inherently adaptable, can evolve in response to changing requirements or conditions. This adaptability ensures that the simulation remains relevant and accurate throughout its lifecycle. The service aims to seamlessly connect traditional design approaches with the advanced requirements of contemporary aircraft structures. It places a strong emphasis on probabilistic design and predictive manufacturing, which are fundamental principles of the CAELESTIS project. Understanding the multifaceted needs of aerospace professionals, this service offers unpar- alleled adaptability. Users have the autonomy to select their desired simulation software for each workflow, ensuring compatibility and relevance across a spectrum of applications. Beyond choosing software, users can set various parameters, creating a customized simulation experience that fits their specific needs. An important point of this service is its adeptness at internally parallelizing the generated workflows using PyCOMPSs [Tej+17] [Bad+15]. This feature not only optimizes computational processes, ensuring efficient utilization of HPC resources, but also positions the service, and by extension the CAELESTIS project, as a prime contender for integration into top-tier simulation systems. Through this research, and with the support and insights from the CAELESTIS project, we endeavor to pioneer a robust, flexible, and dynamic toolset. This toolset has the potential to redefine how aerospace experts approach the design and manufacturing of next-generation aircraft structures, leveraging the might of HPC and the agility of dynamic workflows. |
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