Internal accounting practices at Whitbread & Company c.1890-1925

This paper examines internal accounting practices at Whitbread & Company from c. 1890 to 1925. At this time, there was an increasing interest in cost accounting, but there is little detailed extant research on general internal accounting practices of firms. The brewing sector, we suggest, is a potentially fruitful realm to further our knowledge of this time. Drawing on the Whitbread brewery archival records, we chart the internal accounting practices of the company. Our findings reveal a stable set of accounting practices, focused mainly on bookkeeping, although the firm’s auditor produced some reports which may have been useful for management decision-making. We argue these practices were highly institutionalised, and seemingly resistant to external forces present in the company’s environment

GridPP: development of the UK computing Grid for particle physics

The GridPP Collaboration is building a UK computing Grid for particle physics, as part of the international effort towards computing for the Large Hadron Collider. The project, funded by the UK Particle Physics and Astronomy Research Council (PPARC), began in September 2001 and completed its first phase 3 years later. GridPP is a collaboration of approximately 100 researchers in 19 UK university particle physics groups, the Council for the Central Laboratory of the Research Councils and CERN, reflecting the strategic importance of the project. In collaboration with other European and US efforts, the first phase of the project demonstrated the feasibility of developing, deploying and operating a Grid-based computing system to meet the UK needs of the Large Hadron Collider experiments. This note describes the work undertaken to achieve this goal

A new mechanism for increasing density peaking in tokamaks: improvement of the inward particle pinch with edge E x B shearing

Developing successful tokamak operation scenarios, as well as confident extrapolation of present-day knowledge requires a rigorous understanding of plasma turbulence, which largely determines the quality of the confinement. In particular, accurate particle transport predictions are essential due to the strong dependence of fusion power or bootstrap current on the particle density details. Here, gyrokinetic turbulence simulations are performed with physics inputs taken from a JET power scan, for which a relatively weak degradation of energy confinement and a significant density peaking is obtained with increasing input power. This way physics parameters that lead to such increase in the density peaking shall be elucidated. While well-known candidates, such as the collisionality, previously found in other studies are also recovered in this study, it is furthermore found that edge E x B shearing may adopt a crucial role by enhancing the inward pinch. These results may indicate that a plasma with rotational shear could develop a stronger density peaking as compared to a non-rotating one, because its inward convection is increased compared to the outward diffusive particle flux as long as this rotation has a significant on E x B flow shear stabilization. The possibly significant implications for future devices, which will exhibit much less torque compared to present day experiments, are discussed

Role of fast ion pressure in the isotope effect in JET L-mode plasmas

This paper presents results of JET ITER-like wall L-mode experiments in hydrogen and deuterium (D) plasmas, dedicated to the study of the isotope dependence of ion heat transport by determination of the ion critical gradient and stiffness by varying the ion cyclotron resonance heating power deposition. When no strong role of fast ions in the plasma core is expected, the main difference between the two isotope plasmas is determined by the plasma edge and the core behavior is consistent with a gyro-Bohm scaling. When the heating power (and the fast ion pressure) is increased, in addition to the difference in the edge region, also the plasma core shows substantial changes. The stabilization of ion heat transport by fast ions, clearly visible in D plasmas, appears to be weaker in H plasmas, resulting in a higher ion heat flux in H with apparent anti-gyro-Bohm mass scaling. The difference is found to be caused by the different fast ion pressure between H and D plasmas, related to the heating power settings and to the different fast ion slowing down time, and is completely accounted for in non-linear gyrokinetic simulations. The application of the TGLF quasi-linear model to this set of data is also discussed

First principles and integrated modelling achievements towards trustful fusion power predictions for JET and ITER

Predictability of burning plasmas is a key issue for designing and building credible future fusion devices. In this context, an important effort of physics understanding and guidance is being carried out in parallel to JET experimental campaigns in H and D by performing analyses and modelling towards an improvement of the understanding of DT physics for the optimization of the JET-DT neutron yield and fusion born alpha particle physics. Extrapolations to JET-DT from recent experiments using the maximum power available have been performed including some of the most sophisticated codes and a broad selection of models. There is a general agreement that 11-15 MW of fusion power can be expected in DT for the hybrid and baseline scenarios. On the other hand, in high beta, torque and fast ion fraction conditions, isotope effects could be favourable leading to higher fusion yield. It is shown that alpha particles related physics, such as TAE destabilization or fusion power electron heating, could be studied in ITER relevant JET-DT plasmas

Deep neural networks for plasma tomography with applications to JET and COMPASS

Convolutional neural networks (CNNs) have found applications in many image processing tasks, such as feature extraction, image classification, and object recognition. It has also been shown that the inverse of CNNs, so-called deconvolutional neural networks, can be used for inverse problems such as plasma tomography. In essence, plasma tomography consists in reconstructing the 2D plasma profile on a poloidal cross-section of a fusion device, based on line-integrated measurements from multiple radiation detectors. Since the reconstruction process is computationally intensive, a deconvolutional neural network trained to produce the same results will yield a significant computational speedup, at the expense of a small error which can be assessed using different metrics. In this work, we discuss the design principles behind such networks, including the use of multiple layers, how they can be stacked, and how their dimensions can be tuned according to the number of detectors and the desired tomographic resolution for a given fusion device. We describe the application of such networks at JET and COMPASS, where at JET we use the bolometer system, and at COMPASS we use the soft X-ray diagnostic based on photodiode arrays

Interpretative and predictive modelling of Joint European Torus collisionality scans

Transport modelling of Joint European Torus (JET) dimensionless collisionality scaling experiments in various operational scenarios is presented. Interpretative simulations at a fixed radial position are combined with predictive JETTO simulations of temperatures and densities, using the TGLF transport model. The model includes electromagnetic effects and collisions as well as (E)over-right-arrow x (b)over-right-arrow shear in Miller geometry. Focus is on particle transport and the role of the neutral beam injection (NBI) particle source for the density peaking. The experimental 3-point collisionality scans include L-mode, and H-mode (D and H and higher beta D plasma) plasmas in a total of 12 discharges. Experimental results presented in (Tala et al 2017 44th EPS Conf.) indicate that for the H-mode scans, the NBI particle source plays an important role for the density peaking, whereas for the L-mode scan, the influence of the particle source is small. In general, both the interpretative and predictive transport simulations support the experimental conclusions on the role of the NBI particle source for the 12 JET discharges