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[ONLINE] From Building to City Energy Simulation
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Description
This course is organised in cooperation with CoE HiDALGO2, NCC Czechia and NCC Germany,
Annotation
This training course, delivered by experts from HiDALGO2 CoE, provides a comprehensive pathway from understanding building-level energy dynamics to performing city-scale energy simulations. Participants will gain hands-on experience using the Ktirio Urban Building framework to integrate GIS, vegetation, scenario, and weather data, enabling high-fidelity modeling of energy consumption and environmental impact. The course emphasizes optimization of building envelopes and systems, leveraging HPC resources for efficient large-scale simulations, and mastering data management platforms to store, retrieve, and analyze simulation results. Attendees will learn to interpret and communicate modeling outputs effectively to guide design decisions and support stakeholder engagement in urban planning and sustainable development projects.
Benefits for the attendees: what will they learn
- Comprehensive Modeling Workflow: Master an end-to-end process for building and city energy simulations using Ktirio tools.
- Data Preparation Expertise: Gain hands-on experience in preparing and processing complex GIS, scenario, and weather datasets for robust simulations.
- Performance Assessment and Optimization: Acquire the ability to assess, interpret, and improve energy performance across diverse urban settings.
- Scalability and Efficiency: Learn to leverage HPC resources and data management platforms to handle large-scale simulations and streamline workflows.
- Validate, interpret, and communicate simulation results to inform design and policy decisions.
Target Audience
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Researchers, Scientists, and Engineers aiming to streamline HPC workflows.
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HPC Administrators or DevOps professionals seeking automation strategies on clusters.
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Software Developers looking to improve reproducibility and performance for scientific workloads.
Level
beginner, intermediate
Language
English
Prerequisites
- Basic Command-Line Proficiency: Comfort with navigating file systems, running commands, and handling data in a Linux environment.
- Introductory HPC Concepts: A general understanding of high-performance computing workflows and job submission.
- Basic Building/Urban Planning Knowledge: A foundational grasp of building structures and urban layouts can help participants better understand the modeling scenarios.
Technical requirements:
Ktirio Urban Building Framework
- Purpose: Main platform for building and city-scale energy simulations, including solar mask computations.
Ktirio GUI
- Purpose: Preparing and integrating GIS, vegetation, scenario, and weather data for simulations.
Python (for scripting and automation, optional for advanced users)
- Purpose: Automating data processing, batch simulations, and post-processing results.
HPC / Remote Access Tools
- SSH client (PuTTY for Windows, terminal for Linux/macOS), SFTP clients
- Purpose: Accessing High-Performance Computing resources for large-scale simulations.
Data Management Platforms
- CKAN
- Purpose: Storing, retrieving, and managing simulation data efficiently.
Spreadsheet or Visualization Tools
- Paraview (for advanced simulation visualization)
- Purpose: Post-processing, analyzing, and communicating results.
Tutors
Christophe Prud'homme - Professor in Applied Mathematics since September 2012 at the University of Strasbourg, France and from 2006 to 2012 in Grenoble. He founded Cemosis and is a manager and contributor to Feel++, an open-source framework for solving PDEs and complex problems. Feel++ is a building block for the Urban Building pilot. His expertise lies in Modeling, Simulation, Optimisation, and High-Performance Computing. He has been involved in numerous courses and tutorials on scientific computing, HPC, and open-source software development. He designed the CI/CD for the Urban Building pilot with automated deployment on EuroHPC systems.
Philippe Pinçon is a Research Software Engineer at Cemosis. He began his career in the field of medical digital simulation in 2021 and joined Cemosis in 2023 with the primary mission of developing the Ktirio Urban Building framework as part of the HiDALGO2 project. He is responsible for modeling physical building models and developing the city's energy simulation code. He manages the connection between input data such as weather data, geographic information, building and environment meshes, and physical thermal models to orchestrate digital energy simulations of buildings and cities.
Gwennolé Chappron is a thermal engineer and architect based in Strasbourg, France. He is affiliated with Cemosis, the Strasbourg Modeling and Simulation Center, and collaborates with the IRMA (Institute of Research in Mathematics and Applications) UMR 7501 at the University of Strasbourg. Within the Modeling and Control team, he contributes to projects involving high-performance computing (HPC), and urban building energy modeling. His work includes participation in the HiDALGO2 project, focusing on advancements in urban building energy simulation. He is also involved in the development of the Ktirio Urban Building framework, a computational platform designed to enhance city energy simulations through continuous integration and continuous deployment (CI/CD) innovations on EuroHPC systems.
Javier Cladellas is a Junior Research Software Engineer at Cemosis. He has been working as a developer at Cemosis since 2023. In particular, he has focused on developing a sensor measurement database for data validation and assimilation for the UB pilot in the European project Hidalgo2. Javier is also the main developer of the feelpp.benchmarking framework, conceived for benchmarking applications on HPC systems.
Vincent Chabannes has been a Research Engineer at Cemosis in the Institute of Mathematical Research (IRMA) of Strasbourg since 2016. He is in charge of the computing infrastructure department and is one of the main developers of the Feel++ and Ktirio software. Vincent obtained his PhD in applied mathematics in 2013. The thesis focused on developing algorithms for the numerical simulation of blood flows, with particular emphasis on fluid-structure interaction modelling and high-performance computing.
Acknowledgements
Co-funded by the European Union. This work has received funding from the European High Performance Computing Joint Undertaking (JU) and Poland, Germany, Spain, Hungary, France under grant agreement number: 101093457.
This project has received funding from the European High-Performance Computing Joint Undertaking (JU) under grant agreement No 101101903. The JU receives support from the Digital Europe Programme and Germany, Bulgaria, Austria, Croatia, Cyprus, Czech Republic, Denmark, Estonia, Finland, Greece, Hungary, Ireland, Italy, Lithuania, Latvia, Poland, Portugal, Romania, Slovenia, Spain, Sweden, France, Netherlands, Belgium, Luxembourg, Slovakia, Norway, Türkiye, Republic of North Macedonia, Iceland, Montenegro, Serbia. This project has received funding from the Ministry of Education, Youth and Sports of the Czech Republic.
This course was supported by the Ministry of Education, Youth and Sports of the Czech Republic through the e-INFRA CZ (ID:90254).
All presentations and educational materials of this course are provided under the Creative Commons Attribution-ShareAlike 4.0 International (CC BY-SA 4.0) license.
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