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PhD project: Shaping turbulence with smart particles


Can we design turbulence? Turbulence is everywhere and yet our fundamental understanding and capabilities to control it remain limited. It is a remarkable property of turbulence that, rather irrespective of the large-scale forcing mechanism, it rapidly tends to restore a universal homogeneous and isotropic state at smaller scales. This tendency to universality severely hinders our capability to modulate turbulence by acting on few (large-scale) degrees of freedom. This program will enter an unexplored terrain and design non-universal turbulence employing “smart” particles capable of applying appropriate small-scale forcing. It will moreover shed light on the physics of complex-shaped particles dispersed in turbulent flows as occurring in nature, take e.g. pollen, plant seeds, fish, bacteria, algae, phytoplankton or sediments. Deeper understanding of these systems will open up the way to technological applications.
In this project a systematic investigation of the dynamics of chiral particles in turbulence is planned by means of tracking of chiral particles, produced by 3D printing technology, and by means of flow velocimetry (PTV, LDV) in well controlled turbulent flows in the Twente water channel, the Twente mass and heat transfer water tunnel, the Twente turbulent Taylor-Couette facility, Boiling Twente Taylor-Couette facility, and the new homogeneous isotropic turbulence facility. 3D printed particles with chiral will be produced and accurately tracked (position and orientation) under well controlled turbulent flow conditions in our world-class turbulence facilities. The influence of fluid inertia on the angular dynamics of almost neutrally buoyant or light particles is an open theoretical question. In this project the center of mass and rotational dynamics of neutrally buoyant and inertial chiral particles will be investigated as a function of the most relevant particle/flow parameters. These include turbulence intensity, particle shape, particle size, and particle density. Typical questions that we want to answer include: how do particles of different sizes influence turbulence? Can the coupling between particle and fluid alter the helicity balance of the turbulent flow? By means of increasing the particle volume fraction we plan to investigate the coupling between particles and flow up to volume fractions of the order of 10%.
To summarize: world class flow facilities, world class high speed imaging, advanced algorithms and analysis to modify turbulence!
More details can be found here:


You have a background in applied physics, aerospace engineering, or mechanical engineering, or in a closely related discipline. You have strong communication skills, including fluency in written and spoken English. You are enthusiastic and highly motivated to do a PhD. Experimental experience and experience in image and data analysis required. Knowledge of (convolutional) neural networks is a plus.

Ons aanbod

• We want you to play a key role in an ambitious project in an inspiring and stimulating international work environment.
• We provide excellent mentorship and a stimulating, modern research environment with world-class research facilities.
• You will have an employment contract for the duration of 4 years and can participate in all employee benefits the university offers.
• You will be embedded in a dynamic research group with colleagues working on similar topics.
• Additionally, the University of Twente is a green campus with excellent facilities and resources for professional and personal development, and offers a wide variety of sports facilities.
• You will follow a high-quality personalized educational program.
• The research will result in a PhD thesis at the end of the employment period.
• We strive for diversity and fairness in hiring.

Informatie en aanmelding

Applicants should be in the possession of a master degree in physics, aerospace engineering, mechanical engineering, or closely related field. Applications should provide:
• A motivation letter describing why you want to apply for this precise position.
• Description of your research interests.
• A detailed CV.
• Academic transcripts from your Bachelor's and Master's degrees.
• Name and email addresses of at least two visible references who are willing to send a letter of recommendation on your behalf.
• An interview with a scientific presentation on your previous work will be part of the interview process.
Potential applicants are encouraged to apply to both Prof. D. Lohse and Assist.Prof. S. Huisman.

The closing date of the vacancy is 31 December 2020.

Over de organisatie

Universiteit Twente (UT)

Universiteit Twente (UT) is het nieuwe decennium ingegaan met een ambitieuze, nieuwe visie, missie en strategie. Als ‘de ultieme people-first technische universiteit' breiden we onze High Tech Human Touch-filosofie en de unieke rol die deze ons in de samenleving toekent snel uit. Alles wat we doen is gericht op maximale impact op mens, samenleving en verbindingen door duurzaam gebruik van wetenschap en technologie. Met onze open, inclusieve en ondernemende houding willen wij bijdragen aan de ontwikkeling van een eerlijke, digitale en duurzame samenleving. Deze houding doordesemt alles wat we doen en is aanwezig in alle afdelingen en faculteiten van de UT. Voortbouwend op onze rijke traditie in het samenvoegen van technische en sociale wetenschappen, richten we ons op vijf onderscheidende onderzoeksdomeinen: Gepersonaliseerde ‘healthtech'; Intelligente productiesystemen; Slimme materialen; De digitale samenleving; en Een weerbare, veerkrachtige wereld.

Als werkgever biedt Universiteit Twente werk dat ertoe doet. Wij rusten je toe om nieuwe mogelijkheden te creëren voor jezelf en voor onze samenleving. Je wordt bij ons deel van een toonaangevende technische universiteit met toenemende, positieve maatschappelijke impact. We bieden een open, inclusieve en ondernemende sfeer, waarin we je stimuleren om gezonde keuzes te maken, bijvoorbeeld via onze flexibele, aanpasbare arbeidsvoorwaarden.

PhD project: Shaping turbulence with smart particles
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