Velocity-space sensitivity of the time-of-flight neutron spectrometer at JET

The velocity-space sensitivities of fast-ion diagnostics are often described by so-called weight functions. Recently, we formulated weight functions showing the velocity-space sensitivity of the often dominant beam-target part of neutron energy spectra. These weight functions for neutron emission spectrometry (NES) are independent of the particular NES diagnostic. Here we apply these NES weight functions to the time-of-flight spectrometer TOFOR at JET. By taking the instrumental response function of TOFOR into account, we calculate time-of-flight NES weight functions that enable us to directly determine the velocity-space sensitivity of a given part of a measured time-of-flight spectrum from TOFOR

Relationship of edge localized mode burst times with divertor flux loop signal phase in JET

A phase relationship is identified between sequential edge localized modes (ELMs) occurrence times in a set of H-mode tokamak plasmas to the voltage measured in full flux azimuthal loops in the divertor region. We focus on plasmas in the Joint European Torus where a steady H-mode is sustained over several seconds, during which ELMs are observed in the Be II emission at the divertor. The ELMs analysed arise from intrinsic ELMing, in that there is no deliberate intent to control the ELMing process by external means. We use ELM timings derived from the Be II signal to perform direct time domain analysis of the full flux loop VLD2 and VLD3 signals, which provide a high cadence global measurement proportional to the voltage induced by changes in poloidal magnetic flux. Specifically, we examine how the time interval between pairs of successive ELMs is linked to the time-evolving phase of the full flux loop signals. Each ELM produces a clear early pulse in the full flux loop signals, whose peak time is used to condition our analysis. The arrival time of the following ELM, relative to this pulse, is found to fall into one of two categories: (i) prompt ELMs, which are directly paced by the initial response seen in the flux loop signals; and (ii) all other ELMs, which occur after the initial response of the full flux loop signals has decayed in amplitude. The times at which ELMs in category (ii) occur, relative to the first ELM of the pair, are clustered at times when the instantaneous phase of the full flux loop signal is close to its value at the time of the first ELM

Closed-form solutions for batch settling height from model settling flux functions

A novel approach for relating suspension batch settling data (settling height vs time) to model settling flux functions is presented. The approach exploits a new closed-form solution relating settling height and time for a very simple functional form of the settling flux. The simple form in question employs a so-called hindered settling factor (a key material property in suspension rheology) that is taken to be a straight-line function of the solids fraction. The closed-form solution for settling height and time has a parametric dependence on the slope and intercept of the above-mentioned (straight line) hindered settling property: thus a functional relationship between batch settling height and suspension material property parameters is established. Moreover by adjusting the slope and intercept parameters, the closed-form solutions for settling height vs time can be matched to batch settling experimental data, and thereby the settling flux can be directly obtained. Unlike classical approaches for determining settling flux functions from batch settling data (i.e. Kynch theory), nowhere does the new approach require data for settling velocity: this gives it an in-built robustness to experimental noise compared to any approach that obtains experimental settling velocities via finite differences of settling heights, since such velocities tend to be far more noisy than the settling heights themselves. In a typical physical system, a straight-line relationship between hindered settling factor and solids volume fraction will only be a reasonable approximation over a very restricted domain of solids fraction. However, over a wider domain, it is possible to approximate the hindered settling factor vs solids fraction dependence via a sequence of straight-line relations, each taken over a narrow interval of solids fraction. A functional form for settling flux is thereby obtained, useful for suspension dewatering calculations and engineering equipment design for suspension/sludge processing. The novel approach for determining settling flux has been applied both to experimental and synthetic batch settling data, and has performed robustly

A simplified parameter extraction technique using batch settling data to estimate suspension material properties in dewatering applications

Batch settling tests are considered in order to obtain dewatering material properties of suspensions/sludges towards the low end of the range of solids fractions. Plausible functional forms are considered for fitting batch settling test (height vs. time) data. In particular, power law and exponential decay functions are shown to be reasonable fits to simulated synthetic batch settling data. These forms are subsequently employed to reconstruct functional relationships between a settling flux function and suspension solids fraction. The functional relationships so obtained are found to be faithful representations of the flux function used to generate the simulated settling data, with improved agreement being achieved by restricting the interval of solids fraction across which the reconstruction is performed. The results suggest that general features only (and not fine details) of batch settling curves are required to reconstruct settling flux functions. In the particular case where power law fits are employed to describe the settling height data, an analytic formula can be derived linking the settling flux function explicitly and directly to the power law fitting parameters. This simplifies immensely the technique for extracting parameters for the settling flux. When applied to real experimental data, errors arising from using the power law fits tend to be small compared to those inherent in the experimental measurements themselves