Toroidal flow measurements of impurity ions in QUEST ECH plasmas using multiple viewing chords emission spectroscopy

A spectroscopic system with multiple viewing chords was developed for QUEST (Q-shu University Experiment with Steady-State Spherical Tokamak) to measure the spatial distribution of ion toroidal velocities in discharges sustained by electron cyclotron resonance heating (ECH). Twenty-four viewing chords were aligned in the midplane and C III emission line spectra were measured for three types of ECH discharge under different magnetic field configurations. By applying an inversion method to the measured spectra, we evaluated the radial distributions of C2+ ion emissivity, temperature, and toroidal velocity. The error in the evaluated velocity was estimated to be less than 5 km/s. It was found that the velocity depends on the magnetic field configuration

Towards learning and verifying invariants of cyber-physical systems by code mutation

Cyber-physical systems (CPS), which integrate algorithmic control with physical processes, often consist of physically distributed components communicating over a network. A malfunctioning or compromised component in such a CPS can lead to costly consequences, especially in the context of public infrastructure. In this short paper, we argue for the importance of constructing invariants (or models) of the physical behaviour exhibited by CPS, motivated by their applications to the control, monitoring, and attestation of components. To achieve this despite the inherent complexity of CPS, we propose a new technique for learning invariants that combines machine learning with ideas from mutation testing. We present a preliminary study on a water treatment system that suggests the efficacy of this approach, propose strategies for establishing confidence in the correctness of invariants, then summarise some research questions and the steps we are taking to investigate them.Comment: Short paper accepted by the 21st International Symposium on Formal Methods (FM 2016