ELM-induced transient tungsten melting in the JET divertor

The original goals of the JET ITER-like wall included the study of the impact of an all W divertor on plasma operation (Coenen et al 2013 Nucl. Fusion 53 073043) and fuel retention (Brezinsek et al 2013 Nucl. Fusion 53 083023). ITER has recently decided to install a full-tungsten (W) divertor from the start of operations. One of the key inputs required in support of this decision was the study of the possibility of W melting and melt splashing during transients. Damage of this type can lead to modifications of surface topology which could lead to higher disruption frequency or compromise subsequent plasma operation. Although every effort will be made to avoid leading edges, ITER plasma stored energies are sufficient that transients can drive shallow melting on the top surfaces of components. JET is able to produce ELMs large enough to allow access to transient melting in a regime of relevance to ITER.

Transient W melt experiments were performed in JET using a dedicated divertor module and a sequence of I-P = 3.0 MA/B-T = 2.9 T H-mode pulses with an input power of P-IN = 23 MW, a stored energy of similar to 6 MJ and regular type I ELMs at Delta W-ELM = 0.3 MJ and f(ELM) similar to 30 Hz. By moving the outer strike point onto a dedicated leading edge in the W divertor the base temperature was raised within similar to 1 s to a level allowing transient, ELM-driven melting during the subsequent 0.5 s. Such ELMs (delta W similar to 300 kJ per ELM) are comparable to mitigated ELMs expected in ITER (Pitts et al 2011 J. Nucl. Mater. 415 (Suppl.) S957-64).

Although significant material losses in terms of ejections into the plasma were not observed, there is indirect evidence that some small droplets (similar to 80 mu m) were released. Almost 1 mm (similar to 6 mm(3)) of W was moved by similar to 150 ELMs within 7 subsequent discharges. The impact on the main plasma parameters was minor and no disruptions occurred. The W-melt gradually moved along the leading edge towards the high-field side, driven by j x B forces. The evaporation rate determined from spectroscopy is 100 times less than expected from steady state melting and is thus consistent only with transient melting during the individual ELMs. Analysis of IR data and spectroscopy together with modelling using the MEMOS code Bazylev et al 2009 J. Nucl. Mater. 390-391 810-13 point to transient melting as the main process. 3D MEMOS simulations on the consequences of multiple ELMs on damage of tungsten castellated armour have been performed.

These experiments provide the first experimental evidence for the absence of significant melt splashing at transient events resembling mitigated ELMs on ITER and establish a key experimental benchmark for the MEMOS code.

How fragmented was the British Holocene wildwood? Perspectives on the “Vera” grazing debate from the fossil beetle record

The reconstruction and structure of the European Holocene “wildwood” has been the focus of considerable academic debate. The ability of palaeoecological data and particularly pollen analysis to accurately reflect the density of wildwood canopy has also been widely discussed. Fossil insects, as a proxy for vegetation and landscape structure, provide a potential approach to address this argument. Here, we present a review and re-analysis of 36 early and mid-Holocene (9500-2000 cal BC) sub-fossil beetle assemblages from Britain, examining percentage values of tree, open ground and dung beetles as well as tree host data to gain an insight into vegetation structure, the role of grazing animals in driving such structure and establish independently the importance of different types of trees and associated shading in the early Holocene “wildwood”. Open indicator beetle species are persistently present over the entire review period, although they fluctuate in importance. During the early Holocene (9500-6000 cal BC), these indicators are initially high, at levels which are not dissimilar to modern data from pasture woodland. However, during the latter stages of this and the next period, 6000-4000 cal BC, open ground and pasture indicators decline and are generally low compared with previously. Alongside this pattern, we see woodland indicators generally increase in importance, although there are significant local fluctuations. Levels of dung beetles are mostly low over these periods, with some exceptions to this pattern, especially towards the end of the Mesolithic and in floodplain areas. Host data associated with the fossil beetles indicate that trees associated with lighter canopy conditions such as oak, pine, hazel and birch are indeed important components of the tree canopy during the earlier Holocene (c. 9500-6000 cal BC), in accordance with much of the current pollen literature. Beetles associated with more shade-tolerant trees (such as lime and elm) become more frequent in the middle Holocene (6000-4000 cal BC) suggesting that at this stage the woodland canopy was less open than previously, although open ground and pasture areas appear to have persisted in some locations. The onset of agriculture (4000-2000 cal BC) coincides with significant fluctuations in woodland composition and taxa. This is presumably as a result of human impact, although here there are significant regional variations. There are also increases in the amounts of open ground represented and especially in the levels of dung beetles present in faunas, suggesting there is a direct relationship between the activities of grazing animals and the development of more open areas. One of the most striking aspects of this review is the variable nature of the landscape suggested by the palaeoecological data, particularly but not exclusively with the onset of agriculture: some earlier sites indicate high variability between levels of tree-associated species on the one hand and the open ground beetle fauna on the other, indicating that in some locations, open areas were of local significance and can be regarded as important features of the Holocene landscape. The role of grazing animals in creating these areas of openness was apparently minimal until the onset of the Neolithic.

Fast automatic two-stage nonlinear model identification based on the extreme learning machine

It is convenient and effective to solve nonlinear problems with a model that has a linear-in-the-parameters (LITP) structure. However, the nonlinear parameters (e.g. the width of Gaussian function) of each model term needs to be pre-determined either from expert experience or through exhaustive search. An alternative approach is to optimize them by a gradient-based technique (e.g. Newton’s method). Unfortunately, all of these methods still need a lot of computations. Recently, the extreme learning machine (ELM) has shown its advantages in terms of fast learning from data, but the sparsity of the constructed model cannot be guaranteed. This paper proposes a novel algorithm for automatic construction of a nonlinear system model based on the extreme learning machine. This is achieved by effectively integrating the ELM and leave-one-out (LOO) cross validation with our two-stage stepwise construction procedure [1]. The main objective is to improve the compactness and generalization capability of the model constructed by the ELM method. Numerical analysis shows that the proposed algorithm only involves about half of the computation of orthogonal least squares (OLS) based method. Simulation examples are included to confirm the efficacy and superiority of the proposed technique.

A multi-output two-stage locally regularized model construction method using the extreme learning machine

This paper investigates the construction of linear-in-the-parameters (LITP) models for multi-output regression problems. Most existing stepwise forward algorithms choose the regressor terms one by one, each time maximizing the model error reduction ratio. The drawback is that such procedures cannot guarantee a sparse model, especially under highly noisy learning conditions. The main objective of this paper is to improve the sparsity and generalization capability of a model for multi-output regression problems, while reducing the computational complexity. This is achieved by proposing a novel multi-output two-stage locally regularized model construction (MTLRMC) method using the extreme learning machine (ELM). In this new algorithm, the nonlinear parameters in each term, such as the width of the Gaussian function and the power of a polynomial term, are firstly determined by the ELM. An initial multi-output LITP model is then generated according to the termination criteria in the first stage. The significance of each selected regressor is checked and the insignificant ones are replaced at the second stage. The proposed method can produce an optimized compact model by using the regularized parameters. Further, to reduce the computational complexity, a proper regression context is used to allow fast implementation of the proposed method. Simulation results confirm the effectiveness of the proposed technique. © 2013 Elsevier B.V.

Playing free: an ethnography of Brazilian free improvisers

In this article I investigate the practice of free music improvisation in Brazil. The reflections and findings presented here are derived from research conducted as part of a four months Higher Education Academy (HEA, UK) Fellowship, carried out between February and June 2014. The aim was to enquire whether or how the practice of free improvisation is taught in the Brazilian higher education system.
As part of this ethnographic study visits to the following universities were scheduled:
The Federal University of Rio de Janeiro - UFRJ
The Universidade Federal do Estado do Rio de Janeiro (UNIRIO)
The University of São Paulo - USP
The Federal University of Minas Gerais – UFMG
The Federal University of Bahia – UFBA.
The Federal University of Rio Grande do Norte in Natal (UFRN) and
The ELM, the Escola Livre de Música in Unicamp.

I discuss here some general background thinking to the research process, specifically recalling the work of French composer and educator Alain Savouret. I proceed to examine the improvisational spirit, the improvisatory worldmaking approach (the ‘jeitinho brasileiro’) that is often considered to be integral to the Brazilian way of life. In the final part of the article I discuss applied ethnographic methodologies, including the design of questions that were used for over 50 video interviews with Brazilian musicians during the research. I conclude with a final reflection on the video interviews with a specific focus on whether free improvisation can be taught, and the importance of listening in the context of free improvisation practices.

Progress at JET in integrating ITER-relevant core and edge plasmas within the constraints of an ITER-like wall

This paper reports the progress made at JET-ILW on integrating the requirements of the reference ITER baseline scenario with normalized confinement factor of 1, at a normalized pressure of 1.8 together with partially detached divertor whilst maintaining these conditions over many energy confinement times. The 2.5 MA high triangularity ELMy H-modes are studied with two different divertor configurations with D-gas injection and nitrogen seeding. The power load reduction with N seeding is reported. The relationship between an increase in energy confinement and pedestal pressure with triangularity is investigated. The operational space of both plasma configurations is studied together with the ELM energy losses and stability of the pedestal of unseeded and seeded plasmas. The achievement of stationary plasma conditions over many energy confinement times is also reported.

Extreme learning machines for virtual metrology and etch rate prediction

Virtual metrology (VM) aims to predict metrology values using sensor data from production equipment and physical metrology values of preceding samples. VM is a promising technology for the semiconductor manufacturing industry as it can reduce the frequency of in-line metrology operations and provide supportive information for other operations such as fault detection, predictive maintenance and run-to-run control. Methods with minimal user intervention are required to perform VM in a real-time industrial process. In this paper we propose extreme learning machines (ELM) as a competitive alternative to popular methods like lasso and ridge regression for developing VM models. In addition, we propose a new way to choose the hidden layer weights of ELMs that leads to an improvement in its prediction performance.