11 research outputs found
Climate-Invariant Machine Learning
Data-driven algorithms, in particular neural networks, can emulate the
effects of unresolved processes in coarse-resolution climate models when
trained on high-resolution simulation data; however, they often make large
generalization errors when evaluated in conditions they were not trained on.
Here, we propose to physically rescale the inputs and outputs of machine
learning algorithms to help them generalize to unseen climates. Applied to
offline parameterizations of subgrid-scale thermodynamics in three distinct
climate models, we show that rescaled or "climate-invariant" neural networks
make accurate predictions in test climates that are 4K and 8K warmer than their
training climates. Additionally, "climate-invariant" neural nets facilitate
generalization between Aquaplanet and Earth-like simulations. Through
visualization and attribution methods, we show that compared to standard
machine learning models, "climate-invariant" algorithms learn more local and
robust relations between storm-scale convection, radiation, and their synoptic
thermodynamic environment. Overall, these results suggest that explicitly
incorporating physical knowledge into data-driven models of Earth system
processes can improve their consistency and ability to generalize across
climate regimes.Comment: 12+18 pages, 8+12 figures, 2+2 tables in the main text +
supplementary information. Submitted to PNAS on December 14th, 202
Cardiac Complications of Vascular-surgery Can Be Predicted By Pharmacological Stress Echocardiography
W1761 Inhibition of NF-κB in Colon Cancer Cells Prevents Peritoneal Dissemination Through Polarisation of Tumor-Associated Macrophages Towards an M1-Like Phenotype
557 TNF-α-Induced Long-Term NF-κB Activation in Intestinal Epithelial Cells: Evidence for Autophagic Degradation of IκBα
A Manifesto for Shadow Places: re-imagining and co-producing connections for justice in an era of climate change
M1808 Analysis of the IL-6/STAT3/AKT Signalling Pathways in Patients With Inflammatory Bowel Disease: Effect of Disease Activity and Duration
DIII-D research advancing the physics basis for optimizing the tokamak approach to fusion energy
Funding Information: This material is based upon work supported by the US Department of Energy, Office of Science, Office of Fusion Energy Sciences, using the DIII-D National Fusion Facility, a DOE Office of Science user facility, under Awards DE-FC02-04ER54698 and DE-AC52-07NA27344. Publisher Copyright: © 2022 IAEA, Vienna.DIII-D physics research addresses critical challenges for the operation of ITER and the next generation of fusion energy devices. This is done through a focus on innovations to provide solutions for high performance long pulse operation, coupled with fundamental plasma physics understanding and model validation, to drive scenario development by integrating high performance core and boundary plasmas. Substantial increases in off-axis current drive efficiency from an innovative top launch system for EC power, and in pressure broadening for Alfven eigenmode control from a co-/counter-I p steerable off-axis neutral beam, all improve the prospects for optimization of future long pulse/steady state high performance tokamak operation. Fundamental studies into the modes that drive the evolution of the pedestal pressure profile and electron vs ion heat flux validate predictive models of pedestal recovery after ELMs. Understanding the physics mechanisms of ELM control and density pumpout by 3D magnetic perturbation fields leads to confident predictions for ITER and future devices. Validated modeling of high-Z shattered pellet injection for disruption mitigation, runaway electron dissipation, and techniques for disruption prediction and avoidance including machine learning, give confidence in handling disruptivity for future devices. For the non-nuclear phase of ITER, two actuators are identified to lower the L-H threshold power in hydrogen plasmas. With this physics understanding and suite of capabilities, a high poloidal beta optimized-core scenario with an internal transport barrier that projects nearly to Q = 10 in ITER at ∼8 MA was coupled to a detached divertor, and a near super H-mode optimized-pedestal scenario with co-I p beam injection was coupled to a radiative divertor. The hybrid core scenario was achieved directly, without the need for anomalous current diffusion, using off-axis current drive actuators. Also, a controller to assess proximity to stability limits and regulate β N in the ITER baseline scenario, based on plasma response to probing 3D fields, was demonstrated. Finally, innovative tokamak operation using a negative triangularity shape showed many attractive features for future pilot plant operation.Peer reviewe
Overview of the JET results
Since the installation of an ITER-like wall, the JET programme has focused on the consolidation of ITER design choices and the preparation for ITER operation, with a specific emphasis given to the bulk tungsten melt experiment, which has been crucial for the final decision on the material choice for the day-one tungsten divertor in ITER. Integrated scenarios have been progressed with the re-establishment of long-pulse, high-confinement H-modes by optimizing the magnetic configuration and the use of ICRH to avoid tungsten impurity accumulation. Stationary discharges with detached divertor conditions and small edge localized modes have been demonstrated by nitrogen seeding. The differences in confinement and pedestal behaviour before and after the ITER-like wall installation have been better characterized towards the development of high fusion yield scenarios in DT. Post-mortem analyses of the plasma-facing components have confirmed the previously reported low fuel retention obtained by gas balance and shown that the pattern of deposition within the divertor has changed significantly with respect to the JET carbon wall campaigns due to the absence of thermally activated chemical erosion of beryllium in contrast to carbon. Transport to remote areas is almost absent and two orders of magnitude less material is found in the divertor