Raytracing modelling of Parabolic Trough systems for optical analysis in IPH processes yield

Overview

Solar parabolic trough collectors (PTCs) are a proven and competitive technology for Industrial Process Heat (IPH) generation. As with other concentrating solar technologies, PTCs are affected by soiling — the deposition of airborne dust and pollutants on reflective surfaces — which degrades optical efficiency and directly impacts power generation yield, O&M costs, and cleaning scheduling. Unlike flat reflectors, PTCs present a curved geometry subject to continuous tracking motion, varying tilt angles, and complex local aerodynamics, all of which govern particle deposition in ways that existing soiling models do not capture. Developing physics-based soiling models tailored to PTCs is therefore a necessary step towards reliable optical simulation for line-focusing CST technologies.

Research engagement

The student will engage with a literature review of existing soiling deposition models and Monte Carlo ray-tracing frameworks applicable to parabolic trough collectors. They will work with physics-based simulation tools and experimental field data collected at the industry partner site (Mars Petcare), gaining exposure to both computational modelling and real plant validation.

Research activities

The student will extend existing flat-reflector soiling deposition models to the curved PTC geometry, accounting for tilt angle, continuous tracking motion, and local aerodynamic effects. They will integrate the resulting deposition model with a Monte Carlo ray-tracing framework to simulate optical efficiency degradation under varying atmospheric and soiling conditions. Cleaning strategy optimisation and yield estimates will be derived from the simulation outputs. The student will work closely with the supervising research group at QUT and collaborate with industry partner Mars Petcare for model validation against field measurements.

Research skills

The student will develop advanced coding skills in Python and/or Matlab, with specific experience in physics-based modelling, Monte Carlo simulation, and optical system analysis. They will gain practical experience in model validation using experimental data, and develop analytical skills in performance assessment and optimisation relevant to concentrating solar thermal systems for industrial applications.

Outcomes

The main outcome is a validated integrated simulation framework coupling soiling deposition with ray-tracing for PTC optical analysis. A well-documented codebase and a written report of all activities performed are also expected. The framework will directly inform cleaning strategy optimisation and yield estimation for PTC-based IPH plants.

Skills and experience

The ideal candidate should have a strong background in coding (Python preferred and/or Matlab), optical modelling or ray-tracing, energy conversion systems, and fluid mechanics or aerodynamics. Curiosity and willingness to engage with both modelling and experimental data are essential.

Start date

2 November, 2026

End date

19 February, 2027

Location

QUT Gardens Point campus

Additional information

The student will be supported at every stage of the project. Previously developed soiling models and ray-tracing tools will be made available as a starting point. Collaboration with industry partner Mars Petcare may provide access to real plant data for model validation, with potential for further funding and research opportunities arising from the partnership.

Keywords

• Industrial Process Heat
• Solar Energy
• Ray Tracing
• Optimization

Contact

Giovanni Picotti

0437361646

g.picotti@qut.edu.au