40 research outputs found

    First Wall Heat Load Control Design for ITER with a Model-Based Approach

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    The design of real time heat load protection functions for the ITER tokamak first wall (FW) plasma-facing components (PFCs) requires the development of simplified, but reliable control-oriented models. The dynamics of interest in this case encompasses slow changes in plasma shape or transient increases in wall power loading. For this purpose, this study presents a new lightweight framework for simulating the FW thermal response during a plasma discharge, validated against higher fidelity codes and developed in a MATLAB/Simulink environment specifically for rapid prototyping and testing of control schemes. This innovative tool allows the ITER FW heat load controller to be designed in the plasma control system simulation platform (PCSSP) following a model-based approach, where a dynamical model of the physical process to control is an integral part of the controller synthesis procedure

    Improved Plasma Vertical Position Control on TCV Using Model-Based Optimized Controller Synthesis

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    Elongated plasmas lead to improved performance in tokamaks but make the plasma prone to vertical instability, which requires active feedback control, a critical issue for future fusion reactors. Vertical control was optimized for the TCV tokamak by applying modern control theory to electromagnetic models for the plasma-vessel-coils dynamics. Two different optimal combinations of poloidal field coils for vertical control actuation are derived from linear plasma response models and used on different timescales for controlling the plasma vertical position. On fast timescales, the priority is input minimization, while on long timescales position control is designed to be compatible with shape control. A structured H-infinity design extending classical H-infinity to fixed-structure control systems was subsequently applied to obtain an optimized controller using all available coils for position control. Closed-loop performance improvement was demonstrated in dedicated TCV experiments, showing a reduction of input requirement for stabilizing the same plasma, thus reducing the risk of power supply saturation and consequent loss of vertical control. This novel algorithm is adaptable to different plasma equilibria as it is designed for model-based automated coil selection and controller tuning, thus avoiding extensive experimental gain scans when performing plasma discharges in TCV. The presented technique is general and can be applied to any present tokamak with independent coils or for the design of future tokamak magnetic control systems.SP

    Strategy to systematically design and deploy the ITER plasma control system: A system engineering and model-based design approach

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    The paper details the process of developing the ITER Plasma Control System (PCS), that is, how to design and deploy it systematically, in the most efficient and effective manner. The integrated nature of the ITER PCS, with its multitude of coupled control functions, and its long-term development, calls for a different approach than the design and short-term deployment of individual controllers. It requires, in the first place, a flexible implementation strategy and system architecture that allows system re-configuration and optimization throughout its development. Secondly, a model-based system engineering approach is carried out, for the complete PCS development, i.e. both its design and deployment. It requires clear definitions for both the PCS role and its functionality, as well as definitions of the design and deployment process itself. The design and deployment process is shown to allow tracing the relationships of the many individual design and deployment aspects, such as system requirements, assumed operation use-cases and response models, and eventually verification and functional validation of the system design. The functional validation will make use of a dedicated PCS simulation platform that includes the description of the control function design as well as plant, actuator and sensor models that enable the simulation of these functions. By establishing a clear understanding of the interconnected steps involved in designing, implementing, commissioning, and operating the system, a more systematic approach is achieved. This ensures the completion of a comprehensive design that can be deployed efficiently, hence preventing the loss of precious operational time needed to debug and retune control functions and more importantly avoiding tokamak discharge disruptions.SP

    Accuracy of Preoperative Lung Ultrasound Score for the prediction of Major Adverse Cardiac Events in elderly patients undergoing HIP Surgery under Spinal Anesthesia: the LUSHIP multicenter observational prospective study

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    Background and objective: We hypothesize that lung ultrasound scores (LUS) can help stratify the cardiac risk of elderly patients undergoing orthopedic surgery for hip fracture, adding value to the Revised Cardiac Risk Index (RCRI), the American Society of Anesthesiologists Physical Status (ASA-PS) and the National Surgical Quality Improvement Program Myocardial infarction and Cardiac arrest (NSQIP-MICA). Methods: Prospective, observational multicenter study of 11 Italian hospitals on patients aged >65 years with hip fractures needing urgent surgery. Subjects with major adverse cardiovascular events (MACE) in the previous 6 months or with ongoing acute heart failure were excluded. Trained anesthesiologists obtained preoperative LUS scores during preoperative evaluation. ROC curve analysis and comparison were used to evaluate test accuracy. Results: A total of 877 patients were enrolled in the study period. 108 MACE events occurred in 98 patients, with an overall incidence of 11.2%. LUS score was higher in complicated than non-complicated patients, 11.6 ± 6.64 vs. 4.97 ± 4.90 (p < 0.001). Preoperative LUS score ≥8 showed both better AUC (0.78) and accuracy (0.76) in predicting MACE than the RCRI scores (p < 0.001), MICA scores (p = 0.001) and ASA classes (p < 0.001). LUS sensitivity was 0.71, specificity was 0.76, negative predictive value was 0.95. LUS score ≥8 showed an OR for MACE of 5.81[95% CI 3.55-9.69] at multivariate analysis. 91 patients (10.4%) experienced postoperative pneumonia showing a preoperative LUS score higher in the non-pneumonia group, p < 0.001. Conclusions: The preoperative LUS score, with its high negative predictive value, could improve patients' risk stratification when used alone or add further value to the RCRI score
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