
Projects
Hessian scientists of various disciplines are using High Performance Computers for their research.
Hessian scientists of various disciplines are using High Performance Computers for their research.
Displaying 121 - 150 of 227
Reinforcement learning methods for robotics are increasingly successful due to the constant development of better policy ...
DNA-PKcs is a gateway protein of the Non-Homologous End Joining DNA Repair Pathway. Which is the process of repairing ...
The MD method is suitable for studying the behavior of liquid molecular systems. According to past investigations in the ...
Empirical performance modeling is a proven instrument to analyze the scaling behavior of HPC applications. Using a set ...
Engine knock is initiated by auto-ignition in the unburned mixture ahead of the flame front, the so-called end-gas. Thus ...
Spray cooling is a very effective method for cooling of electronic devices. The study of the impact of single and ...
This project aims into testing the ability of the scale-adaptive turbulence model christened “Instability Sensitive ...
Droplet impingement and spreading are of particular relevance for various technical applications, including inkjet ...
Combustion engines are a common means to power various types of machinery. Despite the declining role of technical ...
This project is concerned with promoting a more efficient usage of the HPC Systems. The two major technologies used to ...
To combat climate change effectively, the use of renewable energy must increase. However, the supply of renewable energy ...
Aerodynamic sound contributes significantly to the noise emission of high-speed applications such as trains, aircraft ...
The formation of pollutants in direct injection engines is a field of research with high practical impact. Against this ...
3D computational fluid dynamics (CFD) simulations are nowadays an established method in science and a tool in industrial ...
Among the major sources of energy supply, pulverized coal combustion (PCC) will remain one most dominant contributors in ...
Model-based value expansion methods promise to improve the quality of value function targets and, thereby, the ...
Reinforcement Learning (RL) has proven to be an empirically very successful approach to solving sequential decision ...
The Nonparametric Off-Policy Policy Gradient (NOPG) is a policy gradient algorithm to solve reinforcement learning tasks ...
The underlying research project deals with the flow accelerated corrosion and erosion in cooling systems of combustion ...
Nowadays, the design and optimization of fluidized beds are primarily based on experimental investigations which are ...
Field-Programmable Gate Arrays (FPGA) contain programmable logic elements that can accommodate application-specific ...
The aim of the project is to develop a new family of optimization algorithms to handle convex constraints and evaluate ...
FPGA cards are increasingly deployed to cloud data centers and made available to users as platform for the ...
Many technical applications in chemistry engineering are multiphase flows as they contain entrained air or effects such ...
Not only in automotive and aviation industries, but also in shipping the engine manufacturer are forced by new ...
Precise models of the system dynamics are crucial for model-based control and reinforcement learning (RL) in autonomous ...
The underlying research project deals with the flow accelerated corrosion and erosion in cooling systems of combustion ...
Deep Reinforcement Learning can solve difficult high dimensional tasks, by exploiting the expressive representation ...
The high pressure turbine design is strongly affected by the flow in the upstream combustor. Very high temperatures ...
Recurrent State-space models (RSSMs) are highly expressive models for learning patterns in time series data and system ...