Projects
Hessian scientists of various disciplines are using High Performance Computers for their research.
Projects
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Projekte
Displaying 1 - 30 of 43
Atomic Scale Modeling of Coherent Phase Transitions in Energy Storage Materials
Hydrogen has emerged as a crucial element in the pursuit of decarbonization and the transition to a sustainable energy ...
Engineering SciencesMaterials Science
Machine Learning Application in Automotive Catalysts
The computational resources of the Lichtenberg HPC were used in this project to train physics informed machine learning ...
Natural SciencesChemical Solid State and Surface Research
Multiscale Modelling of Cement-Based Materials III
The project seeks to create a comprehensive model linking nanoscale phenomena to larger-scale behaviors to better ...
Engineering SciencesConstruction Engineering and Architecture
Parallel Finite Element Methods for Complex Flows of Complex Fluids
The objective of this ongoing project is the continuous development and advancement of effective simulation methods for ...
Engineering SciencesHeat Energy Technology, Thermal Machines, Fluid Mechanics-
Amortized Variational Inference by Policy Search
Variational inference with Gaussian mixture models (GMMs) can be used to learn highly tractable approximations of ...
Engineering SciencesComputer Science 
Computer-Aided Analysis of Time-Lapse Microscopy Data II
During development and adult homeostasis, cells in our bodies need to constantly integrate internal and external ...
Life SciencesBasic Research in Biology and Medicine
CYWARN – Entwicklung von Strategien und Technologien zur Analyse und Kommunikation der Sicherheitslage im Cyberraum II
The increase in complex cyber-attacks illustrates the vulnerability of society and information infrastructure. In ...
Engineering SciencesComputer Science
Detecting Suitcase Damages With Artificial Intelligence – IT-Project Lufthansa
Artificial intelligence is currently developing faster than ever and introduces many different possibilities. Our client ...
Engineering SciencesComputer Science-
Gradient-Based Variational Inference by Policy Search
Many problems in machine learning involve inference from intractable distributions. For example, when learning latent ...
Engineering SciencesComputer Science 
Imitation Learning for Lap Time Simulation
In order to facilitate rapid prototyping and testing in the advanced motorsport industry, we consider the problem of ...
Engineering SciencesComputer Science
Improving the Model-Based Prediction of Vibroacoustic Vehicle Properties by Mastering Uncertainty
Vibroacoustic vehicle behavior specifies among others the quality of vehicles and contributes to customer satisfaction ...
Engineering SciencesMechanics and Constructive Mechanical Engineering
Multiscale Modelling of Cement-Based Materials II
The project aims to develop a bridging model that connects the nanoscale to the upscaled levels for understanding the ...
Engineering SciencesConstruction Engineering and Architecture
Predicting Human Similarity Judgments Using Normalizing Flows
Recent work has shown that deep neural networks are able to predict human similarity judgments with high accuracy (e.g ...
Humanities and Social Sciences-
Scientific Machine Learning for Chemical Kinetics
Detailed multi-scale modelling provides in-depth insights into the complex phenomena of catalytic systems that typically ...
Engineering SciencesProcess Engineering, Technical Chemistry 
A Machine-Learning Interatomic Potential for the Si-O System
Nowadays, atomistic simulations are becoming more and more important. Due to the increasing availability of ...
Engineering SciencesMaterials Science
Combining Regenerative and Degenerative Methods in Growing Neural Networks
Neural networks are usually trained with a static architecture. However, the fields of growing and pruning, or ...
Engineering SciencesComputer Science-
Computer-Aided Analysis of Time-Lapse Microscopy Data I
During development and adult homeostasis, cells in our bodies need to constantly integrate internal and external ...
Life Sciences 
CYWARN – Entwicklung von Strategien und Technologien zur Analyse und Kommunikation der Sicherheitslage im Cyberraum
The increase in complex cyber-attacks illustrates the vulnerability of society and information infrastructure. In ...
Engineering SciencesComputer Science-
Generation of Training Data for a Gaussian Process Based Surrogate Model
This project was a follow-up project for our initial project intended at setting up Lichtenberg Cluster for the use ...
Engineering Sciences -
Implementation and Validation of an Approach for Statistical Parameter Calibration
The prediction accuracy of models is affected using deterministic parameters. That is because the uncertainty of these ...
Engineering SciencesMechanics and Constructive Mechanical Engineering 
Multiscale Modelling of Cement-Based Materials
Overall objective of this project is to develop an elementary physical/chemical bridging model for the chemical reaction ...
Engineering SciencesConstruction Engineering and Architecture
Reinforcement of High-Entropy Metallic Glasses: A Molecular Dynamics Study
Since their invention in the 1960s, metallic glasses (MGs) gained great attention due to their high strength and elastic ...
Engineering SciencesMaterials Science-
Sensitivity Analysis of a Complex Multibody System
This project was a follow-up project for our initial project intended at setting up Lichtenberg Cluster for the use ...
Engineering Sciences 
Ab-initio Modeling of Battery Materials
One approach to the realization of safer batteries relies on all solid-state batteries (ASSB) which use a non-flammable ...
Engineering SciencesMaterials Science
Ab-Initio Thermodynamics of Refractory Mo-Si-Ti Phases at High Temperatures
Refractory metal silicide systems like Mo-Si-Ti are expected to be ideal substrates in composite materials for high ...
Engineering SciencesMaterials Science
Multi-Scale Modeling of Additive Manufactured Magnetic Materials
In 2018, Gottschall et al. proposed a multi-stimulit concept for magnetocaloric cooling. [1] The energy consumption ...
Engineering SciencesMaterials Science-
Noise Resilient Empirical Performance Modeling with Deep Neural Networks
Empirical performance modeling is a proven instrument to analyze the scaling behavior of HPC applications. Using a set ...
Engineering SciencesComputer Science 
Probabilistic Power Plant Dispatch Prediction
To model future energy systems and their markets, it is important to understand the underlying dynamics of their ...
Engineering SciencesElectrical Engineering and Information Technology
Testing and Development of Methods for the Calculation of Phase Diagrams of Interatomic Potentials
Understanding the behavior of different materials not only furthers general knowledge, but can also often be used for ...
Natural SciencesStatistical Physics, Soft Matter, Biological Physics, Nonlinear Dynamics
A Gaussian Approximation Potential for Silica
For the understanding of materials it is often necessary to analyse them on the atomic scale. Molecular dynamics is a ...
Engineering SciencesMaterials Science
