Predicting ocean-induced ice-shelf melt rates using deep learning

Through their role in buttressing upstream ice flow, Antarctic ice shelves play an important part in regulating future sea-level change. Reduction in ice-shelf buttressing caused by increased ocean-induced melt along their undersides is now understood to be one of the key drivers of ice loss from the Antarctic ice sheet. However, despite the importance of this forcing mechanism, most ice-sheet simulations currently rely on simple melt parameterisations of this ocean-driven process since a fully coupled ice–ocean modelling framework is prohibitively computationally expensive. Here, we provide an alternative approach that is able to capture the greatly improved physical description of this process provided by large-scale ocean-circulation models over currently employed melt parameterisations but with trivial computational expense. This new method brings together deep learning and physical modelling to develop a deep neural network framework, MELTNET, that can emulate ocean model predictions of sub-ice-shelf melt rates. We train MELTNET on synthetic geometries, using the NEMO ocean model as a ground truth in lieu of observations to provide melt rates both for training and for evaluation of the performance of the trained network. We show that MELTNET can accurately predict melt rates for a wide range of complex synthetic geometries, with a normalised root mean squared error of 0.11 m yr−1 compared to the ocean model. MELTNET calculates melt rates several orders of magnitude faster than the ocean model and outperforms more traditional parameterisations for &gt; 96 % of geometries tested. Furthermore, we find MELTNET's melt rate estimates show sensitivity to established physical relationships such as changes in thermal forcing and ice-shelf slope. This study demonstrates the potential for a deep learning framework to calculate melt rates with almost no computational expense, which could in the future be used in conjunction with an ice sheet model to provide predictions for large-scale ice sheet models.</p

X-ray Tail in NGC 7619

We present new observational results of NGC 7619, an elliptical galaxy with a prominent X-ray tail and a dominant member of the Pegasus group. With Chandra and XMM-Newton observations, we confirm the presence of a long X-ray tail in the SW direction; moreover, we identify for the first time a sharp discontinuity of the X-ray surface brightness in the opposite (NE) side of the galaxy. The density, temperature and pressure jump at the NE discontinuity suggest a Mach number ~1, corresponding to a galaxy velocity of ~500 km s-1, relative to the surrounding hot gas. Spectral analysis of these data shows that the Iron abundance of the hot gaseous medium is much higher (1-2 solar) near the center of NGC 7619 and in the tail extending from the core than in the surrounding regions (< 1/2 solar), indicating that the gas in the tail is originated from the galaxy. The possible origin of the head-tail structure is either on-going ram-pressure stripping or sloshing. The morphology of the structure is more in line with a ram pressure stripping phenomenon, while the position of NGC 7619 at the center of the Pegasus I group, and its dominance, would prefer sloshing.Comment: ApJ accepted to appear in the 2008 December 1 issue; Added discussion on sloshin

Viscoelastic models for ligaments and tendons

Ligaments and tendons serve a variety of important functions in the human body. Many experimental studies have focused on understanding their mechanical behavior, mathematical modeling has also contributed important information. This paper presents a brief review of viscoelastic models that have been proposed to describe the nonlinear and time-dependent behavior of ligaments and tendons. Specific attention is devoted to quasi-linear viscoelasticity (QLV) and to our most recent approach, the single integral finite strain model (SBFS) which incorporates constitutive modeling of microstructural change. An example is given in which the SIFS model is used to describe the viscoelastic behavior of a human patellar tendon

Efficiency of Energy Transduction in a Molecular Chemical Engine

A simple model of the two-state ratchet type is proposed for molecular chemical engines that convert chemical free energy into mechanical work and vice versa. The engine works by catalyzing a chemical reaction and turning a rotor. Analytical expressions are obtained for the dependences of rotation and reaction rates on the concentrations of reactant and product molecules, from which the performance of the engine is analyzed. In particular, the efficiency of energy transduction is discussed in some detail.Comment: 4 pages, 4 fugures; title modified, figures 2 and 3 modified, content changed (pages 1 and 4, mainly), references adde

Passive active neutron radioassay measurement uncertainty for combustible and glass waste matrices

Using a modified statistical sampling and verification approach, total uncertainty of INEL`s Passive Active Neutron (PAN) radioassay system was evaluated for combustible and glass content codes. Waste structure and content of 100 randomly selected drums in each the waste categories were computer modeled based on review of real-time radiography video tapes. Specific quantities of Pu were added to the drum models according to an experimental design. These drum models were then submitted to the Monte Carlo Neutron Photon code processing and subsequent calculations to produce simulated PAN system measurements. The reported Pu masses from the simulation runs were compared with the corresponding input masses. Analysis of the measurement errors produced uncertainty estimates. This paper presents results of the uncertainty calculations and compares them to previous reported results obtained for graphite waste

Effects of Impurities in Random Sequential Adsorption on a One-Dimensional Substrate

We have solved the kinetics of random sequential adsorption of linear $k$-mers on a one-dimensional disordered substrate for the random sequential adsorption initial condition and for the random initial condition. The jamming limits $\theta(\infty, k', k)$ at fixed length of linear $k$-mers have a minimum point at a particular density of the linear $k'$-mers impurity for both cases. The coverage of the surface and the jamming limits are compared to the results for Monte Carlo simulation. The Monte Carlo results for the jamming limits are in good agreement with the analytical results. The continuum limits are derived from the analytical results on lattice substrates.Comment: 9 pages, latex, 1 figure not included, accepted in Phys. Rev.

Regional-scale chemical transport modeling in support of the analysis of observations obtained during the TRACE-P experiment

Data obtained during the TRACE-P experiment is used to evaluate how well the CFORS/STEM-2K1 regional-scale chemical transport model is able to represent the aircraft observations. Thirty-one calculated trace gas and aerosol parameters are presented and compared to the in situ data. The regional model is shown to accurately predict many of the important features observed. The mean values of all the model parameters in the lowest 1 km are predicted within ±30% of the observed values. The correlation coefficients (R) for the meteorological parameters are found to be higher than those for the trace species. For example, for temperature, R \u3e 0.98. Among the trace species, ethane, propane, and ozone show the highest values (0.8 \u3c R \u3c 0.9), followed by CO, SO2, and NOy, NO and NO2 had the lowest values (R \u3c 0.4). Analyses of pollutant transport into the Yellow Sea by frontal events are presented and illustrate the complex nature of outflow. Biomass burning from SE Asia is transported in the warm conveyor belt at altitudes above ∼2 km and at latitudes below 30N. Outflow of pollution emitted along the east coast of China in the postfrontal regions is typically confined to the lower ∼2 km and results in high concentrations with plume-like features in the Yellow Sea. During these situations the model underpredicts CO and black carbon (among other species). An analysis of ozone production in this region is also presented. In and around the highly industrialized regions of East Asia, where fossil fuel usage dominates, ozone is NMHC-limited. South of ∼30-35N, ozone production is NOx-limited, reflecting the high NMHC/NOx ratios due to the large contributions to the emissions from biomass burning, biogenics sources, and biofuel usage in central China and SE Asia. Copyright 2003 by the American Geophysical Union

Condensation and Clustering in the Driven Pair Exclusion Process

We investigate particle condensation in a driven pair exclusion process on one- and two- dimensional lattices under the periodic boundary condition. The model describes a biased hopping of particles subject to a pair exclusion constraint that each particle cannot stay at a same site with its pre-assigned partner. The pair exclusion causes a mesoscopic condensation characterized by the scaling of the condensate size $m_{\rm con}\sim N^\beta$ and the number of condensates $N_{\rm con}\sim N^\alpha$ with the total number of sites $N$. Those condensates are distributed randomly without hopping bias. We find that the hopping bias generates a spatial correlation among condensates so that a cluster of condensates appears. Especially, the cluster has an anisotropic shape in the two-dimensional system. The mesoscopic condensation and the clustering are studied by means of numerical simulations.Comment: 4 pages, 5 figure

Atomic-scale images of charge ordering in a mixed-valence manganite

Transition-metal perovskite oxides exhibit a wide range of extraordinary but imperfectly understood phenomena. Charge, spin, orbital, and lattice degrees of freedom all undergo order-disorder transitions in regimes not far from where the best-known of these phenomena, namely high-temperature superconductivity of the copper oxides, and the 'colossal' magnetoresistance of the manganese oxides, occur. Mostly diffraction techniques, sensitive either to the spin or the ionic core, have been used to measure the order. Unfortunately, because they are only weakly sensitive to valence electrons and yield superposition of signals from distinct mesoscopic phases, they cannot directly image mesoscopic phase coexistence and charge ordering, two key features of the manganites. Here we describe the first experiment to image charge ordering and phase separation in real space with atomic-scale resolution in a transition metal oxide. Our scanning tunneling microscopy (STM) data show that charge order is correlated with structural order, as well as with whether the material is locally metallic or insulating, thus giving an atomic-scale basis for descriptions of the manganites as mixtures of electronically and structurally distinct phases.Comment: 8 pages, 4 figures, 19 reference