Real-Time Control of Tokamak Plasmas: from Control of Physics to Physics-Based Control

Stable, high-performance operation of a tokamak requires several plasma control problems to be handled simultaneously. Moreover, the complex physics which governs the tokamak plasma evolution must be studied and understood to make correct choices in controller design. In this thesis, the two subjects have been merged, using control solutions as experimental tool for physics studies, and using physics knowledge for developing new advanced control solutions. The TCV tokamak at CRPP-EPFL is ideally placed to explore issues at the interface between plasma physics and plasma control, by combining a state-of-the-art digital real-time control system with a flexible and powerful set of actuators, in particular the electron cyclotron heating and current drive system (ECRH/ECCD). This unique experimental platform has been used to develop and test new control strategies for three important and reactor-relevant tokamak plasma physics instabilities, including the sawtooth, the edge localized mode (ELM) and the neoclassical tearing mode (NTM). These control strategies offer new possibilities for fusion plasma control and at the same time facilitate studies of the physics of the instabilities with greater precision and detail in a controlled environment. The period of the sawtooth crash, a periodic MHD instability in the core of a tokamak plasma, can be varied by localized deposition of ECRH/ECCD near the q = 1 surface, where q is the safety factor. Exploiting this known physical phenomenon, a sawtooth pacing controller was developed which is able to precisely control the time of appearance of the next sawtooth crash. It was also shown that each individual sawtooth period can be controlled in real-time. A similar scheme is applied to H-mode plasmas with type-I ELMs, where it is shown that pacing regularizes the ELM period. The regular, reproducible and therefore predictable sawtooth crashes obtained by the sawtooth pacing controller have been used to study the relationship between sawteeth and NTMs. It is known that post-crash MHD activity can provide the "seed" island for an NTM, which then grows under its neoclassical bootstrap drive. Experiments are shown which demonstrate that the seeding of 3/2 NTMs by long sawtooth crashes can be avoided by preemptive, crash-synchronized EC power injection pulses at the q = 3/2 rational surface location. NTM stabilization experiments in which the ECRH deposition location is moved in real-time with steerable mirrors have shown effective stabilization of both 3/2 and 2/1 NTMs, and have precisely localized the deposition location that is most effective. Studies of current-profile driven destabilization of tearing modes in TCV plasmas with significant amounts of ECCD show a great sensitivity to details of the current profile, but failed to identify a stationary region in the parameter space in which NTMs are always destabilized. This suggests that transient effects intrinsically play a role. Next to instability control, the simultaneous control of magnetic and kinetic plasma profiles is another key requirement for advanced tokamak operation. While control of kinetic plasma profiles around an operating point can be handled using standard linear control techniques, the strongly nonlinear physics of the coupled profiles complicates the problem significantly. Even more, since internal magnetic quantities are difficult to measure with sufficient spatial and temporal resolution —even after years of diagnostic development— routine control of tokamak plasma profiles remains a daunting and extremely challenging task. In this thesis, a model-based approach is used in which physics understanding of plasma current and energy transport is embedded in the control solution. To this aim, a new lightweight transport code has been derived focusing on simplicity and speed of simulation, which is compatible with the demands for real-time control. This code has been named RAPTOR (RApid Plasma Transport simulatOR). In a first-of-its-kind application, the partial differential equation for current diffusion is solved in real-time during a plasma shot in the TCV control system using RAPTOR. This concept is known in control terms as a state observer, and it is applied experimentally to the tokamak current density profile problem for the first time. The real-time simulation gives a physics-model-based estimate of key plasma quantities, to be controlled or monitored in real-time by different control systems. Any available diagnostics can be naturally included into the real-time simulation providing additional constraints and removing measurement uncertainties. The real-time simulation approach holds the advantage that knowledge of the plasma profiles is no longer restricted to those points in space and time where they are measured by a diagnostic, but that an estimate for any quantity can be computed at any time. This includes estimates of otherwise unmeasurable quantities such as the loop voltage profile or the bootstrap current distribution. In a first closed-loop experiment, an estimate of the internal inductance resulting from the real-time simulation is feedback controlled, independently from the plasma central temperature, by an appropriate mix of co- and counter- ECCD. As a tokamak plasma evolves from one state to another during plasma ramp-up or ramp-down, the profile trajectories must stay within a prescribed operational envelope delimited by physics instabilities and engineering constraints. Determining the appropriate actuator command sequence to navigate this operational space has traditionally been a trial-and-error procedure based on experience of tokamak physics operators. A computational technique is developed based on the RAPTOR code which can calculate these trajectories based on the profile transport physics model, by solving an open-loop optimal control problem. The solution of this problem is greatly aided by the fact that the code returns the plasma state trajectory sensitivities to input trajectory parameters, a functionality which is unique to RAPTOR. This information can also be used to construct linearized models around the optimal trajectory, and to determine the active constraint, which can be used for time-varying closed-loop controller design. This physics-model-based approach has shown excellent results and holds great potential for application in other tokamaks worldwide as well as in future devices

A mixture of organic acids and thymol protects primary chicken intestinal epithelial cells from Clostridium perfringens infection in vitro

Necrotic enteritis causes economic losses estimated to be up to 6 billion US dollars per year. Clinical and sub-clinical infections in poultry are also both correlated with decreased growth and feed efficiency. Moreover, in a context of increased antibiotic resistance, feed additives with enhanced antimicrobial properties are a useful and increasingly needed strategy. In this study, the protective effects of a blend of thymol and organic acids against the effects of Clostridium perfringens type A (CP) on chicken intestinal epithelial cells were investigated and compared to bacitracin, a widely used antibiotic in poultry production. Primary chicken intestinal epithelial cells were challenged with CP for a total time of 3h to assess the beneficial effect of two doses of citric acid, dodecanoic acid, and thymol-containing blend, and compare them with bacitracin. During the challenge different parameters were recorded, such as transepithelial electrical resistance, cell viability, mRNA expression, and reactive oxygen species production. CP induced inflammation with cytokine production and loss of epithelial barrier integrity. It was also able to induce reactive oxygen species production and increase the caspase expression leading to cellular death. The high dose of the blend acted similarly to bacitracin, preventing the disruptive effects of CP and inducing also an increase in zonula occludens-1 mRNA expression. The low dose only partially prevented the disruptive effects of CP but successfully reduced the associated inflammation. This study shows that the usage of thymol combined with two organic acids can protect primary chicken intestinal epithelial cells from CP-induced damages creating a valid candidate to substitute or adjuvate the antibiotic treatment against necrotic enteritis

Current ramps optimization study with the RAPTOR code

Optimization of the plasma discharge is related to determination of the optimal time evolution of the plasma parameters to reach a specific plasma state taken into account certain physical and technical constraints. The set of plasma parameters which should be optimized consists of the parameters significantly changing the plasma state and can be defined from the different tokamak actuator inputs: plasma current, EC, NBI heating or current drive power, density, etc. In this work we carry out the optimization study of the current ramp down. Numerical optimization of this phase can prescribe evolution of the plasma parameters to terminate plasma as fast as possible and in the same time to avoid disruptions in the real experiments. The simulation is performed with the RAPTOR code. It is a light and fast transport code with a simplified transport model which includes transport equations for electron temperature and poloidal flux. However, this code was constructed assuming a fixed plasma equilibrium, whereas plasma geometry might change during ramp-down phase. Therefore RAPTOR has been extended to include time varying terms. In this way, time varying plasma geometry can be used in the optimization procedure and for example plasma elongation can be an additional parameter for the trajectory optimization. The results of the simulation with the extended transport model and optimization procedure of ramp-down phase of AUG-like plasma parameters are presented

Effects of dietary supplementation with krill meal on pigmentation and quality of flesh of rainbow trout (Oncorhynchus mykiss)

Effects of administration of krill meal and synthetic astaxanthin during the finisher phase of the fattening cycle of rainbow trout on flesh pigmentation and quality traits were studied. The inclusion of krill meal increased the body weight and size and decreased the peri-visceral fat and visceral weight indices. The astaxanthin diet produced the highest accumulation of total carotenoids in the fillet compared to the krill meal diet: the difference was significant after 15 days of feeding (2.50 vs 2.10 mg/kg) till the end of the trial (5.00 vs 4.80 mg/kg). The same pattern was observed for astaxanthin concentration with the highest values in the fillets of fish fed the astaxanthin diet. Fillet lightness (L*) was not affected by trout diets whereas redness (a*) and yellowness (b*) were significantly higher in fish fed the astaxanthin diet until day 30 of the trial. Hue was not affected by feeding, whereas chroma was significantly higher in the fish fed astaxanthin throughout the trial except on day 45 of sampling. Trout fed the krill meal diet had a paler pink-red colour on the SalmoFan scale than those receiving the astaxanthin diet. No significant differences emerged in proximate composition and cholesterol content of trout in the two groups. The fatty acid profile of the fillets reflected the fatty acids of the diets administered to the trout: eicosapentaenoic, docosahexaenoic and docosapentaenoic acids and total n-3 polyunsaturated fatty acids were significantly higher in the fish fed the krill meal

Common peroneal nerve injuries at the knee: outcomes of nerve repair

Background. Common peroneal nerve (CPn) lesion at the knee is one of the most frequent neurologic injury of the lower limb. Among the etiologies there are also open and closed trauma. If direct nerve repair is not possible, nerve grafting is indicated as a primary or delayed procedure. Nerve and tendon transfer are other possible therapeutic options. Material and methods. In this retrospective double center study, 35 patients with post-traumatic CPn lesion at the knee, that underwent surgical repair, were analyzed. Exclusion criteria were severe concomitant neurological pathologies, complex injury of the lower leg including major vessels lesion and or tibial nerve injury. The objective of the study is to demonstrate the degree of foot dorsiflexion recovery based on the type of trauma and the corresponding performed surgery: the Medical Research Council classification (M0-M5) was used as rating scale. Results. There were 23 closed and 12 open injuries. Time of surgery varied from 6 to 11 months after closed trauma, whereas 2 open traumas were explored at emergency and the remaining 10 patients were explored 3 to 9 months after injury. Neurolysis was performed in 12 cases. Neurorraphy was performed in 2 cases. Sural nerve grafting was performed in 21 patients, with a length range of 6-10,5 cm and 4-9 cm for closed and open trauma respectively. Conclusions. Our series confirms that repairs of traumatic CPn injuries have an unfavorable outcome. Motor recovery score ≥ M3 was obtained in only 10 cases (28,57%). Neurolysis and nerve suture show better results than nerve graft alone, although no statistically significant differences emerged; CPn reconstructions with grafts show unsatisfactory results, particularly if the length of the grafts exceeds 6 cm and when patients are treated over 6 months after the trauma. Patients with closed trauma achieve less satisfactory results than those with open injury (13 vs 58%) and this was statistically significant (p < 0.05), so palliative surgery may be indicated as the first surgical approach for these patients to achieve good foot dorsiflexion

Numerical optimization of ramp-down phases for TCV and AUG plasmas

Optimization of the plasma discharge can be defined as determination of an optimal time evolution of the plasma parameters to lead a plasma to a desired state keeping it within the specific limits: physical ones (like the Greenwald density limit, low normalized beta and internal inductance values) and technical ones (like the vertical stability limit). The parameters, time-trajectories of which have to be optimized, are the ones significantly changing the plasma state, and, depending on the optimization goal, can be chosen from a wide range of plasma parameters: plasma current, plasma elongation, EC, NBI heating or current drive power, electron density, etc. Developing non-disruptive termination scenarios is important for safe operation of future tokamaks and especially for ITER since significant heat fluxes to the wall are expected during disruptions because of large amount of energy stored in burning plasmas. Therefore, the main goal of ramp-down optimization is to ramp down a plasma current as fast as possible while avoiding any disruptions. The results of the optimization problem study with the physical and technical limits is presented for TCV and AUG plasmas. The present work was done mainly with the RAPTOR code. The transport model has been extended to include a time-varying plasma equilibrium geometry, increasing the accuracy of full discharge simulations. Due to the design, the RAPTOR code is also an efficient tool for an optimization problem solving. A new ad-hoc transport model has been implemented to the RAPTOR code and tested during this work. Verification of the thermal transport model with simulation of the AUG and TCV full plasma discharges using RAPTOR will be presented

Fast modeling of turbulent transport in fusion plasmas using neural networks

We present an ultrafast neural network (NN) model, QLKNN, which predicts core tokamak transport heat and particle fluxes. QLKNN is a surrogate model based on a database of 300 million flux calculations of the quasilinear gyrokinetic transport model QuaLiKiz. The database covers a wide range of realistic tokamak core parameters. Physical features such as the existence of a critical gradient for the onset of turbulent transport were integrated into the neural network training methodology. We have coupled QLKNN to the tokamak modelling framework JINTRAC and rapid control-oriented tokamak transport solver RAPTOR. The coupled frameworks are demonstrated and validated through application to three JET shots covering a representative spread of H-mode operating space, predicting turbulent transport of energy and particles in the plasma core. JINTRAC-QLKNN and RAPTOR-QLKNN are able to accurately reproduce JINTRAC-QuaLiKiz T i,e and n e profiles, but 3 to 5 orders of magnitude faster. Simulations which take hours are reduced down to only a few tens of seconds. The discrepancy in the final source-driven predicted profiles between QLKNN and QuaLiKiz is on the order 1%-15%. Also the dynamic behaviour was well captured by QLKNN, with differences of only 4%-10% compared to JINTRAC-QuaLiKiz observed at mid-radius, for a study of density buildup following the L-H transition. Deployment of neural network surrogate models in multi-physics integrated tokamak modelling is a promising route towards enabling accurate and fast tokamak scenario optimization, Uncertainty Quantification, and control applications.Comment: 18 pages, 11 figures, Physics of Plasmas, ICDDPS 2019 conference pape