Internship- Development of a Python package with thermal-hydraulic correlations for LMFR – lmth23




Years of experience

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newcleo is a clean and safe nuclear technology company. Privately funded and headquartered in London, UK, newcleo was launched in 2021 to be a disruptor in the field of nuclear energy. Its mission is to generate safe, clean, economic and inexhaustible energy for the world, through a radically innovative combination of existing, accessible technologies.

newcleo is building the next generation system with the goals to:

  1. eliminate the need for geological repositories by using a fast neutron flux avoiding the production of long life radioactive elements;
  2. accelerate the development of new fuel cycles, including MOX (Mixed Pu-U Oxides) and eventually thorium, that provide clean, safe and inexhaustible energy from nuclei and the opportunity to burn the long-lived nuclear waste produced by the old generation of nuclear reactors;
  3. ultimately develop an Accelerator Driven System (ADS), based on the intrinsically safe coupling of a particle accelerator and a sub-critical reactor.

With visionary co-founders, newcleo brings together an international team of senior engineers with deep knowledge of nuclear energy and new recruits with a fresh mindset, working to develop designs based on innovative Lead-cooled Fast Reactors (LFRs). These LFRs will meet the commercial demand for small terrestrial waste-to-energy reactors.

In the UK, newcleo’s immediate focus is on delivering a prototype 30MWe LFR by 2030 followed by an initial battery of 4-6 x 200MWe reactors with deployment in the early 2030s. We are building our team to meet this challenging and exciting objective.

newcleo wants to be the first step toward the evolution of its industry to become fully respectful of people and the environment. To develop a new, sustainable, and completely safe way of generating nuclear energy that will lead humanity to zero emissions, and to the mitigation of global warming.

Reports to (Job Title):

R&D Manager – Codes & Methods

Job Description

To collaborate to newcleo’s experimental campaign of thermal-hydraulic experiments to support the design activities for new LFR units.
A compilation of the available empirical correlations from literature in a single and comprehensive library is currently on-going to characterize heat transfer and thermal-hydraulic phenomena with liquid metals. This library will also collect the results from the future experiments. This internship position focuses on the literature review about the existing correlations and supports the development of this library.
Several empirical correlations are available in literature to describe heat transfer, thermalhydraulics and pressure drop phenomena occurring in presence of liquid metals, which are used as coolant for nuclear fast reactors. Every physical correlation comes with its validity range given in terms of dimensionless numbers, flow conditions, and for particular geometrical configurations. The use of a correlation outside the validity range does not guarantee accurate predictions of the quantity of interest. So a careful check about the correlation’s appropriateness
must be done before use.
Some correlations yield directly dimensionless numbers, expressing the importance of a given phenomenon with respect to other competing ones, like in the case of the Nusselt number. Heat transfer and pressure drop correlations (Darcy factor for instance) are fundamental for the design of heat exchangers, which constitutes a large part of the forthcoming experimental program planned by newcleo. Newcleo is implementing a Python package as unique and standardized entry point for evaluating all the empirical correlations needed for general LMFR applications. Moreover, this package will be used to support the next experimental campaign, including possible implementation of the new correlations arising from it.

Main Activities

During this internship the student will participate to the development of the Python package lmth23 (Liquid-Metal Thermal-Hydraulics). In particular, the correlations for the friction factor and for the Nusselt number in LMFR fuel bundles and once-through heat exchangers with cross-flow will be considered. The first release of the package will provide the desired quantity given the characteristic geometric parameters and coolant velocity at input to calculate the Reynolds number appropriately. In addition to reviewing and implementing the physical correlations, the student will focus on implementation techniques and high quality standards for code development. This will make the package easier to maintain and extend in the future, serving both uses in industry and research. Therefore, the student will develop/consolidate skills in the following aspects of software engineering in Python:
• Object-Oriented programming based on SOLID principles;
• Python Dynamic programming;
• design patterns (template and factory patterns in particular);
• CI/CD pipelines (including regression tests);
• write well-documented code for scientific applications.
The internship will be supervised by an engineer from R&D team of newcleo.

Ideal Background


Master student in Nuclear, Mechanical or Aerospace Engineering; Applied Physics; Informatics
and Computational Sciences.


Fluent Italian and English

Experience / Professional requirements

  • Fundamentals in thermal-hydraulics and heat transfer
  • • Basic knowledge of software programming (previous experience in Python is very appreciated)
  • • Basic knowledge of Linux operative system
  • Experience using git, basic knowledge on liquid metal-cooled fast reactors.
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