Calculations of Energy Losses due to Atomic Processes in Tokamaks with Applications to the ITER Divertor

Reduction of the peak heat loads on the plasma facing components is essential for the success of the next generation of high fusion power tokamaks such as the International Thermonuclear Experimental Reactor (ITER) 1 . Many present concepts for accomplishing this involve the use of atomic processes to transfer the heat from the plasma to the main chamber and divertor chamber walls and much of the experimental and theoretical physics research in the fusion program is directed toward this issue. The results of these experiments and calculations are the result of a complex interplay of many processes. In order to identify the key features of these experiments and calculations and the relative role of the primary atomic processes, simple quasi-analytic models and the latest atomic physics rate coefficients and cross sections have been used to assess the relative roles of central radiation losses through bremsstrahlung, impurity radiation losses from the plasma edge, charge exchange and hydrogen radiation losses from the scrape-off layer and divertor plasma and impurity radiation losses from the divertor plasma. This anaysis indicates that bremsstrahlung from the plasma center and impurity radiation from the plasma edge and divertor plasma can each play a significant role in reducing the power to the divertor plates, and identifies many of the factors which determine the relative role of each process. For instance, for radiation losses in the divertor to be large enough to radiate the power in the divertor for high power experiments, a neutral fraction of 10-3 to 10-2 and an impurity recycling rate of netrecycle of ~ 10^16 s m^-3 will be required in the divertor.Comment: Preprint for the 1994 APSDPP meeting, uuencoded and gzipped postscript with 22 figures, 40 pages

Inclusive B-Meson Production at the LHC in the GM-VFN Scheme

We calculate the next-to-leading-order cross section for the inclusive production of B mesons in pp collisions in the general-mass variable-flavor-number scheme, an approach which takes into account the finite mass of the b quarks. We use realistic evolved non-perturbative fragmentation functions obtained from fits to e+e- data and compare results for the transverse-momentum and rapidity distributions at a center-of-mass energy of 7 TeV with recent data from the CMS Collaboration. We find good agreement, in particular at large values of pT.Comment: Minor changes to the text, accepted for publication in Phys. Rev.

Application of Statistical Learning Control to the Design of a Fixed-Order Controller for a Flexible Beam

This paper shows how probabilistic methods and statistical learning theory can provide approximate solutions to “difficult” control problems. The paper also introduces bootstrap learning methods to drastically reduce the bound on the number of samples required to achieve a performance level. These results are then applied to obtain more efficient algorithms which probabilistically guarantee stability and robustness levels when designing controllers for uncertain systems. The paper includes examples of the applications of these methods

Statistical learning control of delay systems: theory and algorithms

Recently, probabilistic methods and statistical learning theory have been shown to provide approximate solutions to “difficult” control problems. Unfortunately, the number of samples required in order to guarantee stringent performance levels may be prohibitively large. In this paper, using recent results by the authors, a more efficient statistical algorithm is presented. Using this algorithm we design static output controllers for a nonlinear plant with uncertain delay

Estimation of circular statistics in the presence of measurement bias

Background and objective. Circular statistics and Rayleigh tests are important tools for analyzing the occurrence of cyclic events. However, current methods fail in the presence of measurement bias, such as incomplete or otherwise non-uniform sampling. Consider, for example, studying 24-cyclicity but having data not recorded uniformly over the full 24-hour cycle. The objective of this paper is to present a method to estimate circular statistics and their statistical significance even in this circumstance. Methods. We present our objective as a special case of a more general problem: estimating probability distributions in the context of imperfect measurements, a highly studied problem in high energy physics. Our solution combines 1) existing approaches that estimate the measurement process via numeric simulation and 2) innovative use of linear parametrizations of the underlying distributions. We compute the estimation error for several toy examples as well as a real-world example: analyzing the 24-hour cyclicity of an electrographic biomarker of epileptic tissue controlled for state of vigilance. Results. Our method shows low estimation error. In a real-world example, we observed the corrected moments had a root mean square residual less than 0.007. We additionally found that, even with unfolding, Rayleigh test statistics still often underestimate the p-values (and thus overestimate statistical significance) in the presence of non-uniform sampling. Numerical estimation of statistical significance, as described herein, is thus preferable. Conclusions. The presented methods provide a robust solution to addressing incomplete or otherwise non-uniform sampling. The general method presented is also applicable to a wider set of analyses involving estimation of the true probability distribution adjusted for imperfect measurement processes

Tracking control of uncertain systems

Deals with the problem of designing output tracking controllers for uncertain systems. The systems we consider may be non-minimum phase but are restricted to be linear. The problem is motivated by control applications where a desired output trajectory is specified, and the corresponding input to the system is to be found

On the control of a high power backward-wave oscillator using quantifier elimination methods

This paper presents an experimental/theoretical study of methods to identify and control a repetitively-pulsed high power microwave source. A neural network was used to model the system and quantifier elimination (QE) theory is used to search for suitable operating conditions

Statistical controller design for the linear benchmark problem

In this paper some fixed-order controllers are designed via statistical methods for the benchmark problem originally presented at the 1990 American Control Conference. Based on some recent results by the authors, it is shown that the statistical approach is a valid method to design robust controllers. Two different controllers are proposed and their performance are compared with controllers with the same structure, designed using different techniques

Elevated fetal steroidogenic activity in autism

Autism affects males more than females, giving rise to the idea that the influence of steroid hormones on early fetal brain development may be one important early biological risk factor. Utilizing the Danish Historic Birth Cohort and Danish Psychiatric Central Register, we identified all amniotic fluid samples of males born between 1993 and 1999 who later received ICD-10 (International Classification of Diseases, 10th Revision) diagnoses of autism, Asperger syndrome or PDD-NOS (pervasive developmental disorder not otherwise specified) (n=128) compared with matched typically developing controls. Concentration levels of Δ4 sex steroids (progesterone, 17α-hydroxy-progesterone, androstenedione and testosterone) and cortisol were measured with liquid chromatography tandem mass spectrometry. All hormones were positively associated with each other and principal component analysis confirmed that one generalized latent steroidogenic factor was driving much of the variation in the data. The autism group showed elevations across all hormones on this latent generalized steroidogenic factor (Cohen's d=0.37, P=0.0009) and this elevation was uniform across ICD-10 diagnostic label. These results provide the first direct evidence of elevated fetal steroidogenic activity in autism. Such elevations may be important as epigenetic fetal programming mechanisms and may interact with other important pathophysiological factors in autism

Optimal discrete-time control for non-linear cascade systems

In this paper we develop an optimality-based framework for designing controllers for discrete-time nonlinear cascade systems. Specifically, using a nonlinear-nonquadratic optimal control framework we develop a family of globally stabilizing backstepping-type controllers parameterized by the cost functional that is minimized. Furthermore, it is shown that the control Lyapunov function guaranteeing closed-loop stability is a solution to the steady-state Bellman equation for the controlled system and thus guarantees both optimality and stability