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The Motional Stark Effect (MSE) diagnostic will be essential for the study of advanced scenarios on ITER and its design is currently underway. In order meet the ITER MSE diagnostic design requirements, two approaches for the measurement are under consideration. The first is based on standard polarimeter techniques to measure the polarization of the emitted light, whereas the second measures the Stark splitting from which.
The Motional Stark Effect (MSE) diagnostic is unique in its ability to measure the current profile and will be essential in ITER for detailed analysis of Advanced Tokamak (AT) and other types of discharges. However, design of a MSE diagnostic for ITER presents many unique challenges. Among these is optical analysis for the convoluted optical path, required for effective neutron shielding, that employs several reflective optics arranged to form a labyrinth. The geometry of the diagnostic has been laid out and the expected Doppler shifts and channel resolution calculated. A model of the optical train has also been developed based on the Mueller matrix formalism. Unfolding the pitch angle for this complicated geometry is not straightforward and possible methods are evaluated. The CORSICA code is used to model a variety of ITER discharges including start-up, Ipramp and reverse shear. The code also incorporates a synthetic MSE diagnostic that can be used to evaluate different viewing locations and optimize channel locations for the above discharges. Simulation of the optical emission spectrum is also underway.
In this study, the baseline design for the ITER electron cyclotron emission (ECE) diagnostic has entered the detailed preliminary design phase. Two plasma views are planned, a radial view and an oblique view that is sensitive to distortions in the electron momentum distribution near the average thermal momentum. Both views provide high spatial resolution electron temperature profiles when the momentum distribution remains Maxwellian. The ECE diagnostic system consists of the front-end optics, including two 1000 K calibration sources, in equatorial port plug EP9, the 70-1000 GHz transmission system from the front-end to the diagnostics hall, and the ECE instrumentation in the diagnostics hall. The baseline ECE instrumentation will include two Michelson interferometers that can simultaneously measure ordinary and extraordinary mode ECE from 70 to 1000 GHz, and two heterodyne radiometer systems, covering 122-230 GHz and 244-355 GHz. Significant design challenges include 1) developing highly-reliable 1000 K calibration sources and the associated shutters/mirrors, 2) providing compliant couplings between the front-end optics and the polarization splitter box that accommodate displacements of the vacuum vessel during plasma operations and bake out, 3) protecting components from damage due to stray ECH radiation and other intense millimeter wave emission and 4) providing the low-loss broadband transmission system.
Magnetic Fusion Technology describes the technologies that are required for successful development of nuclear fusion power plants using strong magnetic fields. These technologies include: • magnet systems, • plasma heating systems, • control systems, • energy conversion systems, • advanced materials development, • vacuum systems, • cryogenic systems, • plasma diagnostics, • safety systems, and • power plant design studies. Magnetic Fusion Technology will be useful to students and to specialists working in energy research.
Although standard mixed effects models are useful in a range of studies, other approaches must often be used in correlation with them when studying complex or incomplete data. Mixed Effects Models for Complex Data discusses commonly used mixed effects models and presents appropriate approaches to address dropouts, missing data, measurement errors, censoring, and outliers. For each class of mixed effects model, the author reviews the corresponding class of regression model for cross-sectional data. An overview of general models and methods, along with motivating examples After presenting real data examples and outlining general approaches to the analysis of longitudinal/clustered data and incomplete data, the book introduces linear mixed effects (LME) models, generalized linear mixed models (GLMMs), nonlinear mixed effects (NLME) models, and semiparametric and nonparametric mixed effects models. It also includes general approaches for the analysis of complex data with missing values, measurement errors, censoring, and outliers. Self-contained coverage of specific topics Subsequent chapters delve more deeply into missing data problems, covariate measurement errors, and censored responses in mixed effects models. Focusing on incomplete data, the book also covers survival and frailty models, joint models of survival and longitudinal data, robust methods for mixed effects models, marginal generalized estimating equation (GEE) models for longitudinal or clustered data, and Bayesian methods for mixed effects models. Background material In the appendix, the author provides background information, such as likelihood theory, the Gibbs sampler, rejection and importance sampling methods, numerical integration methods, optimization methods, bootstrap, and matrix algebra. Failure to properly address missing data, measurement errors, and other issues in statistical analyses can lead to severely biased or misleading results. This book explores the biases that arise when naïve methods are used and shows which approaches should be used to achieve accurate results in longitudinal data analysis.