Practical trainings, student assistants and theses

Production of electricity by nuclear power plants inevitably generates high-level and long-lived radioactive waste. A solution considered by several nuclear waste management agencies is to store them into deep underground repositories. The principle of such a concept is to provide a multi-barrier system to avoid the release of the radioactive waste through the biosphere for very long time scales (up to hundred thousand of years). It is thus of great importance to be able to characterize both at a macroscopic and a molecular level the different processes (retention, reduction, surface precipitation, etc.) that can take place onto mineral surfaces and thus affect the availability and the mobility of the radionuclides. This information can be inserted in surface complexation models for the description and prediction over a long time-scale of the interaction of pollutants at the solid/liquid interface with several sorbent surfaces. These surface complexation models rely on a thermodynamic description of the solid/water interface and represent a geochemically robust and sound approach to quantify adsorption equilibria.

The solution of adsorption equilibria problems can be reached via Gibbs Free Energy Minimization and/or Law of Mass Action. Standard procedures apply commonly used geochemical software such as FITEQL/PHREEQC coupled to shell optimizers (UCODE, PEST). They are nevertheless subject to numerical instability and/or convergence problems, and to the risk to fall into a local minimum region rather than a global optimum valley. This risk is drastically increased when the number of adjustable parameters becomes higher than 3 or 4. Also the “trial and error” approach within the numerical fitting data can become very fast time consuming.

Thus, the objective of the present work are i) to develop alternative approaches to enable the handling of a high number of adjustable parameters at once, ii) the speed up of the optimizing procedure in order to reduce the time required for the user to reach a satisfactory description of the experimental data.

Your specific tasks:

• Implement a genetic algorithm coupled to Levenberg-Marquardt optimization on a high performance computing cluster,

• Compare the results of with another optimization path, namely Downhill Simplex,

• Find reliable ways to provide realistic uncertainties of the adjustable parameters (e.g. scale sensitivity, Monte-Carlo, etc.).

This internship or assistant position can be used as a basis for a follow-up Research Project, Bachelor or Master thesis.

Good knowledge in python programming and standard optimization routines (Newton-Raphson, Levenberg-Marquardt, etc.) is mandatory.

Students without knowledge in chemistry are also encouraged to apply.

Very good English skills are appreciated.

Duration min. 3 months

Start: from now

Workplace: HZDR, Dresden-Rossendorf

At Helmholtz-Zentrum Dresden-Rossendorf (HZDR), over 1,500 employees from more than 70 nations are conducting cutting-edge research in the fields of ENERGY, HEALTH, and MATERIALS to address the major challenges facing society today.
The Center for Advanced Systems Understanding (CASUS), founded in Görlitz in 2019, is a German-Polish interdisciplinary research center focusing on data-intensive digital systems.
CASUS offers student internships in a wide range of scientific fields. You are welcome to apply and join CASUS if you are interested in gaining knowledge in the following research areas:

• Theoretical Chemistry
• Earth System Science
• Systems Biology
• Digital Health
• Computational Radiation Physics
• Theory of complex systems
• Dynamics of Complex Living Systems
• Machine Learning for Infection and Disease

• Student in computer science, physics, chemistry, or related fields
• Student already enrolled at the university in Germany, Poland or Czech Republic (close exchange and attendance in the office preferable and combined with the moblie working from Germany combinable)
• Eager to learn new skills
• Strong motivation to work in a collaborative environment
• Preliminary experience in code development is an advantage
• Excellent communication skills in English and/or German or Polish

• A vibrant research community in an open, diverse and international work environment
• Scientific excellence and extensive professional networking opportunities
• A wide range of qualification opportunities
• We support a good work-life balance with the possibility of part-time employment, mobile working and flexible working hours
• Either an immediate start or a start in 2024 is possible

Background:

Currently, there is a broad discussion whether ventilation by frequent window opening is sufficient for providing a sufficient amount of fresh air or if technical air purification devices based on e.g. HEPA filters are better solutions for public spaces. Furthermore, there is another discussion ongoing, whether a well-guided laminar flow or a high degree of mixing within a room is more beneficial. The latter, on the one hand distributes the potentially virus-laden aerosols in the whole room, but on the other hand reduces the peak concentrations of these aerosols clouds by magnitudes.

Objectives:

The objective is to perform aerosol propagation experiments and to estimate the potential aerosol inhalation of people in dynamic situations. To achieve this, an aerosol generator will be used in a demonstrator room under different flow conditions. The data from different scenarios will be processed in order to obtain a transference function that can relate the aerosol source with the aerosol receivers.

Tasks:

• Literature survey
• Aerosol experiments in different scenarios.
• Post-processing of the results.

• Student of natural sciences or engineering
• Willingness to conduct experimental work

Duration:

4-6 months

Remuneration:

According to HDZR guidelines