Xicheng Wang

I am a postdoc researcher in the Division of Nuclear Science and Engineering, Department of Physics.

Ph.D. in Nuclear Engineering at KTH, MSc in Nuclear Energy Engineering at Tsinghua University, China; and KTH, Sweden (dual master program).

The safe, efficient, and sustainable use of nuclear power is fundamental to its role in the global transition toward low-carbon energy. Its design and operation must ensure that, under both normal and accidental conditions, nuclear power plants pose no unacceptable risk to the public. Achieving this goal demands a deep understanding of the thermal-hydraulic phenomena that governs reactor behaviors, which are inherently complex, involving multiphase and multi-physics processes across a wide range of spatial and temporal scales. My research is driven by a fundamental question in nuclear power safety: how can we better resolve and predict these phenomena to reduce uncertainties in safety assessment and ensure that risks remain as low as reasonably achievable?

To address this question, I rely on three pillars. (i) I use high-resolution Computational Fluid Dynamics (CFD) and low-resolution system-level codes to analyze the safety-related thermal-hydraulic behavior, supported by systematic sensitivity analysis to identify the most influential parameters. (ii) I design Integral Effects Tests (IETs) to investigate the interaction between multiple phenomena and Separate Effects Tests (SETs) to study individual phenomena. Observations are used to support model development, calibration and validation. (iii) I apply machine learning techniques to uncover hidden patterns within the dataset generated by both numerical and experimental studies.