New algorithm and results for the three-dimensional random field Ising Model

The random field Ising model with Gaussian disorder is studied using a new Monte Carlo algorithm. The algorithm combines the advantanges of the replica exchange method and the two-replica cluster method and is much more efficient than the Metropolis algorithm for some disorder realizations. Three-dimensional sytems of size $24^3$ are studied. Each realization of disorder is simulated at a value of temperature and uniform field that is adjusted to the phase transition region for that disorder realization. Energy and magnetization distributions show large variations from one realization of disorder to another. For some realizations of disorder there are three well separated peaks in the magnetization distribution and two well separated peaks in the energy distribution suggesting a first-order transition.Comment: 24 pages, 23 figure

Prevalence of Dysglycemia Among Coronary Artery Bypass Surgery Patients with No Previous Diabetic History

<p>Abstract</p> <p>Background</p> <p>Dysglycemia is a major risk factor for atherosclerosis. In many patient populations dysglycemia is under-diagnosed. Patients with severe coronary artery disease commonly have dysglycemia and there is growing evidence that dysglycemia, irrespective of underlying history of diabetes, is associated with adverse outcome in coronary artery bypass graft (CABG) surgery patients, including longer hospital stay, wound infections, and higher mortality. As HbA1c is an easy and reliable way of checking for dysglycemia we routinely screen all patients undergoing CABG for elevations in HbA1c. Our hypothesis was that a substantial number of patients with dysglycemia that could be identified at the time of cardiothoracic surgery despite having no apparent history of diabetes.</p> <p>Methods</p> <p>1045 consecutive patients undergoing CABG between 2007 and 2009 had HbA1c measured pre-operatively. The 2010 American Diabetes Association (ADA) diagnostic guidelines were used to categorize patients with no known history of diabetes as having diabetes (HbA1c ≥ 6.5%) or increased risk for diabetes (HbA1c 5.7-6.4%).</p> <p>Results</p> <p>Of the 1045 patients with pre-operative HbA1c measurements, 40% (n = 415) had a known history of diabetes and 60% (n = 630) had no known history of diabetes. For the 630 patients with no known diabetic history: 207 (32.9%) had a normal HbA1c (< 5.7%); 356 (56.5%) had an HbA1c falling in the increased risk for diabetes range (5.7-6.4%); and 67 (10.6%) had an HbA1c in the diabetes range (6.5% or higher). In this study the only conventional risk factor that was predictive of high HbA1c was BMI. We also found a high HbA1c irrespective of history of DM was associated with severe coronary artery disease as indicated by the number of vessels revascularized.</p> <p>Conclusion</p> <p>Among individuals undergoing CABG with no known history of diabetes, there is a substantial amount of undiagnosed dysglycemia. Even though labeling these patients as "diabetic" or "increased risk for diabetes" remains controversial in terms of perioperative management, pre-operative screening could lead to appropriate post-operative follow up to mitigate short-term adverse outcome and provide high priority medical referrals of this at risk population.</p

A control oriented strategy of disruption prediction to avoid the configuration collapse of tokamak reactors

The objective of thermonuclear fusion consists of producing electricity from the coalescence of light nuclei in high temperature plasmas. The most promising route to fusion envisages the confinement of such plasmas with magnetic fields, whose most studied configuration is the tokamak. Disruptions are catastrophic collapses affecting all tokamak devices and one of the main potential showstoppers on the route to a commercial reactor. In this work we report how, deploying innovative analysis methods on thousands of JET experiments covering the isotopic compositions from hydrogen to full tritium and including the major D-T campaign, the nature of the various forms of collapse is investigated in all phases of the discharges. An original approach to proximity detection has been developed, which allows determining both the probability of and the time interval remaining before an incoming disruption, with adaptive, from scratch, real time compatible techniques. The results indicate that physics based prediction and control tools can be developed, to deploy realistic strategies of disruption avoidance and prevention, meeting the requirements of the next generation of devices

Overview of JET results for optimising ITER operation

The JET 2019–2020 scientific and technological programme exploited the results of years of concerted scientific and engineering work, including the ITER-like wall (ILW: Be wall and W divertor) installed in 2010, improved diagnostic capabilities now fully available, a major neutral beam injection upgrade providing record power in 2019–2020, and tested the technical and procedural preparation for safe operation with tritium. Research along three complementary axes yielded a wealth of new results. Firstly, the JET plasma programme delivered scenarios suitable for high fusion power and alpha particle (α) physics in the coming D–T campaign (DTE2), with record sustained neutron rates, as well as plasmas for clarifying the impact of isotope mass on plasma core, edge and plasma-wall interactions, and for ITER pre-fusion power operation. The efficacy of the newly installed shattered pellet injector for mitigating disruption forces and runaway electrons was demonstrated. Secondly, research on the consequences of long-term exposure to JET-ILW plasma was completed, with emphasis on wall damage and fuel retention, and with analyses of wall materials and dust particles that will help validate assumptions and codes for design and operation of ITER and DEMO. Thirdly, the nuclear technology programme aiming to deliver maximum technological return from operations in D, T and D–T benefited from the highest D–D neutron yield in years, securing results for validating radiation transport and activation codes, and nuclear data for ITER

Overview of JET results for optimising ITER operation

The JET 2019–2020 scientific and technological programme exploited the results of years of concerted scientific and engineering work, including the ITER-like wall (ILW: Be wall and W divertor) installed in 2010, improved diagnostic capabilities now fully available, a major neutral beam injection upgrade providing record power in 2019–2020, and tested the technical and procedural preparation for safe operation with tritium. Research along three complementary axes yielded a wealth of new results. Firstly, the JET plasma programme delivered scenarios suitable for high fusion power and alpha particle (α) physics in the coming D–T campaign (DTE2), with record sustained neutron rates, as well as plasmas for clarifying the impact of isotope mass on plasma core, edge and plasma-wall interactions, and for ITER pre-fusion power operation. The efficacy of the newly installed shattered pellet injector for mitigating disruption forces and runaway electrons was demonstrated. Secondly, research on the consequences of long-term exposure to JET-ILW plasma was completed, with emphasis on wall damage and fuel retention, and with analyses of wall materials and dust particles that will help validate assumptions and codes for design and operation of ITER and DEMO. Thirdly, the nuclear technology programme aiming to deliver maximum technological return from operations in D, T and D–T benefited from the highest D–D neutron yield in years, securing results for validating radiation transport and activation codes, and nuclear data for ITER

A control oriented strategy of disruption prediction to avoid the configuration collapse of tokamak reactors

The objective of thermonuclear fusion consists of producing electricity from the coalescence of light nuclei in high temperature plasmas. The most promising route to fusion envisages the confinement of such plasmas with magnetic fields, whose most studied configuration is the tokamak. Disruptions are catastrophic collapses affecting all tokamak devices and one of the main potential showstoppers on the route to a commercial reactor. In this work we report how, deploying innovative analysis methods on thousands of JET experiments covering the isotopic compositions from hydrogen to full tritium and including the major D-T campaign, the nature of the various forms of collapse is investigated in all phases of the discharges. An original approach to proximity detection has been developed, which allows determining both the probability of and the time interval remaining before an incoming disruption, with adaptive, from scratch, real time compatible techniques. The results indicate that physics based prediction and control tools can be developed, to deploy realistic strategies of disruption avoidance and prevention, meeting the requirements of the next generation of devices.Confining plasma and managing disruptions in tokamak devices is a challenge. Here the authors demonstrate a method predicting and possibly preventing disruptions and macroscopic instabilities in tokamak plasma using data from JET

Shattered pellet injection experiments at JET in support of the ITER disruption mitigation system design

A series of experiments have been executed at JET to assess the efficacy of the newly installed shattered pellet injection (SPI) system in mitigating the effects of disruptions. Issues, important for the ITER disruption mitigation system, such as thermal load mitigation, avoidance of runaway electron (RE) formation, radiation asymmetries during thermal quench mitigation, electromagnetic load control and RE energy dissipation have been addressed over a large parameter range. The efficiency of the mitigation has been examined for the various SPI injection strategies. The paper summarises the results from these JET SPI experiments and discusses their implications for the ITER disruption mitigation scheme

Peripheral temperature gradient screening of high-Z impurities in optimised 'hybrid' scenario H-mode plasmas in JET-ILW

Screening of high-Z (W) impurities from the confined plasma by the temperature gradient at the plasma periphery of fusion-grade H-mode plasmas has been demonstrated in the JET-ILW (ITER-like wall) tokamak. Through careful optimisation of the hybrid-scenario, deuterium plasmas with sufficient heating power (greater than or similar to 32 MW), high enough ion temperature gradients at the H-mode pedestal top can be achieved for the collisional, neo-classical convection of the W impurities to be directed outwards, expelling them from the confined plasma. Measurements of the W impurity fluxes between and during edge-localised modes (ELMs) based on fast bolometry measurements show that in such plasmas there is a net efflux (loss) between ELMs but that ELMs often allow some W back into the confined plasma. Provided steady, high-power heating is maintained, this mechanism allows such plasmas to sustain high performance, with an average D-D neutron rate of similar to 3.2 x 10(16) s(-1) over a period of similar to 3 s, after an initial overshoot (equivalent to a D-T fusion power of similar to 9.4 MW), without an uncontrolled rise in W impurity radiation, giving added confidence that impurity screening by the pedestal may also occur in ITER, as has previously been predicted (Dux et al 2017 Nucl. Mater. Energy 12 28-35)

Predictive JET current ramp-up modelling using QuaLiKiz-neural-network

This work applies the coupled JINTRAC and QuaLiKiz-neural-network (QLKNN) model on the ohmic current ramp-up phase of a JET D discharge. The chosen scenario exhibits a hollow T-e profile attributed to core impurity accumulation, which is observed to worsen with the increasing fuel ion mass from D to T. A dynamic D simulation was validated, evolving j, n(e), T-e, T-i, n(Be), n(Ni), and n(W) for 7.25 s along with self-consistent equilibrium calculations, and was consequently extended to simulate a pure T plasma in a predict-first exercise. The light impurity (Be) accounted for Z(eff) while the heavy impurities (Ni, W) accounted for Prad. This study reveals the role of transport on the Te hollowing, which originates from the isotope effect on the electron-ion energy exchange affecting T-i. This exercise successfully affirmed isotopic trends from previous H experiments and provided engineering targets used to recreate the D q-profile in T experiments, demonstrating the potential of neural network surrogates for fast routine analysis and discharge design. However, discrepancies were found between the impurity transport behaviour of QuaLiKiz and QLKNN, which lead to notable T-e hollowing differences. Further investigation into the turbulent component of heavy impurity transport is recommended

New H-mode regimes with small ELMs and high thermal confinement in the Joint European Torus

New H-mode regimes with high confinement, low core impurity accumulation, and small edge-localized mode perturbations have been obtained in magnetically confined plasmas at the Joint European Torus tokamak. Such regimes are achieved by means of optimized particle fueling conditions at high input power, current, and magnetic field, which lead to a self-organized state with a strong increase in rotation and ion temperature and a decrease in the edge density. An interplay between core and edge plasma regions leads to reduced turbulence levels and outward impurity convection. These results pave the way to an attractive alternative to the standard plasmas considered for fusion energy generation in a tokamak with a metallic wall environment such as the ones expected in ITER.&amp; nbsp;Published under an exclusive license by AIP Publishing