Commercial small scale tableting devices are designed to produce tablets from a pre-blended powder bulk. Most devices do not offer flexibility regarding the change of compaction parameters from one tablet to the next one. These parameters can be the compaction force, the compaction speed, and the dwell time, to list some of them. Furthermore, the formulation is also fixed for one batch. In the process we are currently setting up at IPPE, flexibility is an important matter, as we plan to take care of personalized tablets and formulation development. A device supplying the needed flexibility shall be developed in this design practice. The image below provides an idea of how the setup could look like.

The main features shall be:

•    Electronic control of compaction parameters
•    Exchangeable compaction die
•    Variable compaction profile

Your work will include the following points:
•    Mechanical design of the compaction device
•    Selection of components fulfilling the requirements
•    Design of the electronic control cycle
•    Assembling and testing of the device

We offer

• High scientific and industrial relevance (the approach involving this dosing process could speed up the development in pharmaceutical industry and allow to produce personalized medicine)
• Support from the IPPE project team.
• Desk and office space

Contact:
Andreas Kottlan, andreas.kottlannoSpam@tugraz.at, 0316-873-30419
Starting date: as soon as possible

The fact that human beings differ from each other, regarding their physiology, pathology and environment suggests, that not everyone can be treated using the same medication. Therefore, a trend towards personalized medicine is observable. This trend brings up some challenges, as it comes to the production of tablets. The dose of the Active Pharmaceutical Ingredient (API) as well as the amount of any excipient needs to be dosed accurately, for each individual tablet.

The development of a device being capable to do so, is the goal of this thesis. As the dosing shall be done gravimetrically, the dosing unit will contain a feeder and a weighing cell. A scheme of the set-up and its features can be seen below.

Your work will include the following points:
•    Picking a development environment (LabView, Arduino/Raspberry Pi, …)
•    Picking a weighing cell with sufficient accuracy and fitting dynamic properties
•    Integration of weighing cell and feeder in an environment for control and data acquisition
•    Investigation of the feeding/dosing characteristics of the set-up
•    Development of a self-adjusting dose algorithm

We offer
•    High scientific and industrial relevance (the approach involving this dosing process could speed up the development in pharmaceutical industry and allow to produce personalized medicine)
•    Support from the IPPE project team and Prof. Horn from IRT
•    Desk and office space

Contact:
Andreas Kottlan, andreas.kottlannoSpam@tugraz.at, 0316-873-30419
Starting date: as soon as possible 2020

Sonic mixing is a relatively new approach for mixing various systems. The process is used to some extend in pharmaceutical industry to produce powder mixtures and pastes. To achieve a satisfying mixing quality, the system is exposed to vibration with high acceleration and high amplitudes in means of travel. This is commercially realized by using a system working at resonance frequency to minimize the power input.

We aim for a much smaller system size, i.e. the mass of single tablet. This allows us to get rid of the need for a system operated at resonance. Therefore, the frequency can be varied to achieve the most effective mixing process. A schematic sketch of the setup can be seen in figure 1.

This thesis shall bring insight to some specific points:
•    How do the operating parameters, i.e. frequency and amplitude affect the flow pattern within the mixing vessel?
•    How does the “flow regime” within the mixing chamber affect the mixing performance?
•    How do different powders react to different operating parameters?
•    Is it possible to find a robust mode of operation which provides satisfying results for various powder systems?
•    Can coating or granulation processes be done using this setup?

The investigation on these topics shall be done using an existing experimental setup, which can be modified to meet arising requirements. The student shall elaborate a design of experiments which covers the relevant operating range of the used vibration generator and accounts for different powder blends. Once defined, the mixing experiments are to be carried out. The blends, produced in this way, need to be analysed. The search for meaningful analysis methods is part of this work.

We offer
•    High scientific and industrial relevance (the approach involving this mixing process could speed up the development in pharmaceutical industry and allow to produce personalized medicine)
•    Support from the IPPE project team
•    Desk and office space

Contact:
Andreas Kottlan, andreas.kottlannoSpam@tugraz.at, 0316-873-30419
Starting date: as soon as possible

Background
The Institute of Process and Particle Engineering is a world leader in the development of simulation tools for industrial-scale bioprocessing units. For example, our current code can model processes in large-scale bioreactors, up to 200m³.

We are therefore looking for a bachelor
or  master  student  with  engineering
background  (chemical  engineering,
bioprocess  engineering,  physics  or
similar)  interested  in  extending  the
simulation  tool  by  adding  an  adaptive
grid refinement algorithm.

The  simulation  code  currently  uses  a  regular  grid.  For  small  structures,  i.e.  small stirrers, the grid around the structure may be too coarse to resolve fine details, e.g. the fluid jet coming from the stirrer. Hence, the objective of this thesis is to employ a new grid addressing scheme and advanced interpolation methods to be able to define areas with a finer grid efficiently within the simulation code.

The coding is done in C++ in combination with the CUDA library on high-performance graphic cards.

Tasks
      • Find and implement a new grid addressing scheme
      • Research and choose interpolation methods
      • Literature study on test cases to validate the program module
      • Include the validation in the test harness of the code

Requirements
      • Background in chemical or bioprocess engineering, physics or similar
      • Basic biotechnological knowledge
      • Being familiar with thermodynamics, simulation and modeling

What we offer
      • Integration in an internationally leading team
      • Opportunity to be part of a commercialization project
      • Paid master thesis
      • Start of a future career in software creation

Start: Summer/Fall 2019

Contact
Dr. Christian Witz
0316 873 30416
christian.witznoSpam@tugraz.at

Background

The  Institute  of  Process  and  Particle  Engineering  is  a
world leader in the development of  simulation tools for        
industrial-scale  bioprocessing  units.  For  example,  our
current  code  can  model  processes  in  large-scale
bioreactors, up to 200m³.

We are therefore looking for a bachelor or master student
with  engineering  background  (chemical  engineering,
bioprocess engineering, physics or similar) interested in
extending  the  simulation  tool by  adding  highly  efficient
and  fast  models  to  calculate  the  heat  transfer  from
heat jackets, heat exchanger or air bubbles to the fluid
in the reactor by employing dimensionless relations like
the Nusselt number. An algorithm for the convective heat
transport is already included in the code.

The coding is done in C++ in combination with the CUDA library on high-performance graphic cards.

Tasks
      • Implement the respective heat transfer by the heat exchanger, heat jacket or air
        bubbles to the fluid as sources in the convective heat
      • Literature study on test cases to validate the program module
      • Include the validation in the test harness of the code

Requirements
      • Background in chemical or bioprocess engineering, physics or similar
      • Basic biotechnological knowledge
      • Being familiar with thermodynamics, simulation and modeling

What we offer
      • Integration in an internationally leading team
      • Opportunity to be part of a commercialization project
      • Paid master thesis
      • Start of a future career in software creation

Start: Summer/Fall 2019

Contact
Dr. Christian Witz
0316 873 30416
christian.witznoSpam@tugraz.at

Background

The Institute of Process and Particle Engineering is a world leader in the development of simulation tools for industrial-scale bioprocessing units. For example, our current code can model processes in large-scale bioreactors, up to 200m³.

We are therefore looking for design exercise (Konstruktionsübung) student with engineering background (chemical engineering, bioprocess engineering, physics or similar) interested in extending the simulation tool by adding algorithms for the automation of the setup and the post processing of the simulation.

The simulation code currently uses a JSON text file as interface to the user to define the simulation parameters. The task of this exercise is to extend a HTML page with Java Script to create this JSON file. A working example already exists.

The second task is to create Python scripts to control the software Paraview, which is currently used to post process the simulation results (e.g. create videos, images and plots automatically).

Tasks
      • Expand the existing HTML/Java Script page
      • Write the Python scripts necessary to create videos, images, plots with Paraview automatically

Requirements
      • Background in chemical or bioprocess engineering, physics or similar
      • Being familiar with programming, simulation and modeling

What we offer
      • Integration in an internationally leading team
      • Opportunity to be part of a commercialization project
      • Paid design exercise
      • Start of a future career in software creation

Start: Summer/Fall 2019

Contact
Dr. Christian Witz
0316 873 30416
christian.witznoSpam@tugraz.at

Experimental Evaluation of a Particle Fractionator

Current trends in paper and pulp production aim on product diversification covering new markets, i.e. fibre-plastic compounds. Separating fibres and fines (i.e., particles smaller than 200μm) may become a crucial process step in future. Answering to this future need, we developed a novel fractionation device in a collaborative project with industry.

First studies revealed a dependence of the separation performance on key flow parameters, and was investigated by means of high-speed imaging (Figure 1, right panel).

Figure 1: Illustration of the fractionation device. (© Jakob D. Redlinger-Pohn, IPPT, TUG)

Bachelor projects will aim on detail investigations of how the fibre network formation affects separation performance. The bachelor students will receive training in the handling of the fractionator, image recording and post-processing with our existing high-speed camera.

We offer

• high industrial and scientific relevance (i.e., a novel separation process which will be applied in “real-world” trials at a paper mill)
• bleeding edge high-speed camera equipment and image post-processing routines
• desk and office space

Contact

Stefan Radl, radl(at)tugraz.at; 0316 873 30412

The bachelor thesis projects can be started earliest in summer 2018

Current trends in advanced multiphase flow prediction aim at the usage of machine learning algorithms and deep neural networks to improve the accuracy and to speed-up numerical simulations. Overall, it can be expected that these tools (and artificial intelligence, AI, in a wider context) will become an important part of numerical modelling used in chemical engineering applications.

The overarching goal of this Master Thesis project is to increase the speed of gas-particle flow simulations (see the right panel in the Figure below) by using an AI-powered prediction algorithm.

Your tasks will include (i) a literature review on the usage of deep learning in numerical simulations, (ii) an investigation related to key parameters of a neural net structure to speed up a widely-used gas-particle flow simulator, and (iii) application of the improved simulator to a use case. The machine learning and deep neural nets will be based on existing open source AI platforms (e.g., Tensorflow), for which expert knowledge is already available at our institute.

Qualification

• Interest in Computational Fluid Dynamics (CFD), Discrete Element Method (DEM)
• Basics programming skills (Matlab/octave, Python, C/C++ or other), and interest to refine your programming skills during the Master Thesis project

We offer

• Extremely high scientific and industrial relevance
• Introduction to the leading open-source gas-particle simulation tools OpenFOAM® and CFDEM®. Support with the AI platform, as well as with respect to programming.
• Computer power, desk and office space
• Possibility to publish the results and findings in a scientific journal

Contact

Josef Tausendschön: josef.tausendschoennoSpam@tugraz.at, Stefan Radl: radlnoSpam@tugraz.at