Name: Training: Visualization and Analysis of Atomistic Simulation Data in OVITO Event type: Workshop Date: November 15 to 17, 2022 Time: 1pm - 5pm Format: Online via Zoom Target Audience: HPC user Contact Person: Dr. Daniel Utt Registration *More information* Desciption Post-processing and analysis of atomistic simulations are essential steps to extract knowledge from the computed […]
Title: NHR4CES Community Workshop 2023 – Machine Learning in Computational Fluid Dynamics Event type: Workshop Date & Time: February 28, 2023, 1.30pm - 5.30pm and March 1, 2023, 9.00am - 1.30pm Format: Online Contact: office@nhr.tu-darmstadt.de Contact persons: Jonas Seng, Dr. Martin Smuda and Ludovico Nista Registration *More information* Desciption Big data and Machine Learning (ML) […]
Machine Learning (ML) methods are being used frequently in research these days. However, often non-experts in ML are faced with the problem of designing and building highly complex models and ML-environments to utilize useful features that ML brings. A high invest of time is needed to acquire the knowledge required to develop ML-models and the […]
Machine Learning (ML) methods are being used frequently in research these days. However, often non-experts in ML are faced with the problem of designing and building highly complex models and ML-environments to utilize useful features that ML brings. A high invest of time is needed to acquire the knowledge required to develop ML-models and the […]
Machine Learning (ML) methods are being used frequently in research these days. However, often non-experts in ML are faced with the problem of designing and building highly complex models and ML-environments to utilize useful features that ML brings. A high invest of time is needed to acquire the knowledge required to develop ML-models and the […]
Machine Learning (ML) methods are being used frequently in research these days. However, often non-experts in ML are faced with the problem of designing and building highly complex models and ML-environments to utilize useful features that ML brings. A high invest of time is needed to acquire the knowledge required to develop ML-models and the […]
Machine Learning (ML) methods are being used frequently in research these days. However, often non-experts in ML are faced with the problem of designing and building highly complex models and ML-environments to utilize useful features that ML brings. A high invest of time is needed to acquire the knowledge required to develop ML-models and the […]
Machine Learning (ML) methods are being used frequently in research these days. However, often non-experts in ML are faced with the problem of designing and building highly complex models and ML-environments to utilize useful features that ML brings. A high invest of time is needed to acquire the knowledge required to develop ML-models and the […]
Machine Learning (ML) methods are being used frequently in research these days. However, often non-experts in ML are faced with the problem of designing and building highly complex models and ML-environments to utilize useful features that ML brings. A high invest of time is needed to acquire the knowledge required to develop ML-models and the […]
Name: CFD Training Series: Efficient HPC implementation for Lagrangian particle tracking Date: October 26, 2023 Time: 1.00 pm - 5.00 pm Format: hybrid More Information Description Short abstract: In this course, the basics of Lagrangian point particle methods for the application on HPC systems are covered. The course consists of an introduction to […]
Machine Learning (ML) methods are being used frequently in research these days. However, often non-experts in ML are faced with the problem of designing and building highly complex models and ML-environments to utilize useful features that ML brings. A high invest of time is needed to acquire the knowledge required to develop ML-models and the […]
Name: CFD Training Series: Introduction to Turbulence Modeling and Numerical Implementation Date: November 02, 2023 Time: 1.00 pm - 5.00 pm Format: online More Information Description Short abstract: In this course, the introduction to the structural properties of various turbulence modeling concepts (RANS, LES, and Hybrid RANS/LES) including associated equations will be given. […]
