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At least 91 records · Page 5

Bayesian and variational Bayesian approaches for flows in heterogeneous random media

In this paper, we study porous media flows in heterogeneous stochastic media. We propose an efficient forward simulation technique that is tailored for variational Bayesian inversion. As a starting point, the proposed forward simulation technique decomposes the solution into the sum of separable functions (with respect to randomness and the space), where each term is calculated based on a variational approach. This is similar to Proper Generalized Decomposition (PGD). Next, we apply a multiscale technique to solve for each term (as in ) and, further, decompose the random function into 1D fields. As a result, our proposed method provides an approximation hierarchy for the solution as we increase the number of terms in the expansion and, also, increase the spatial resolution of each term. We use the hierarchical solution distributions in a variational Bayesian approximation to perform uncertainty quantification in the inverse problem. We conduct a detailed numerical study to explore the performance of the proposed uncertainty quantification technique and show the theoretical posterior concentration.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Coaxial Ceramic Direct Ink Writing on Heterogenous and Rough Surfaces: Investigation of Core–Shell Interactions

In this work, coaxial conductor–ceramic direct ink writing enables the printing of sensitive or encapsulated materials onto heterogeneous and rough substrates. While encasing the core fluid within a stiff ceramic shell, continuity may be maintained, even while printing onto conventionally challenging substrates. Here, we report the development of a coaxial ceramic direct ink writing suite and explore coflow interrelationships based on microfluidic principles. A coaxial nozzle is designed to facilitate the coextrusion of an alumina shell, whereas indium–tin-oxide inks constitute the core. In this manner, a core–shell ceramic element may be printed onto rough substrates for future high-temperature applications. Colloidal inks are engineered to provide the required rheological and sintering performance. Moreover, flow simulations in conjunction with microfluidic coflow principles are used to explore the coaxial printing processing space, thus controlling the core–shell architectures. Physical modeling is further used to analyze core deformations and eccentricity. As a result, simulations are validated experimentally, and the analyses are used to deposit coaxial ceramic features onto heterogeneous, high-temperature ceramic substrates.

20 FOSSIL-FUELED POWER PLANTS↗

Method of Distributions for Two‐Phase Flow in Heterogeneous Porous Media

Abstract Multiscale heterogeneity and insufficient characterization data for a specific subsurface formation of interest render predictions of multi‐phase fluid flow in geologic formations highly uncertain. Quantification of the uncertainty propagation from the geomodel to the fluid‐flow response is typically done within a probabilistic framework. This task is computationally demanding due to, for example, the slow convergence of Monte Carlo simulations (MCS), especially when computing the tails of a distribution that are necessary for risk assessment and decision‐making under uncertainty. The frozen streamlines method (FROST) accelerates probabilistic predictions of immiscible two‐phase fluid flow problems; however, FROST relies on MCS to compute the travel‐time distribution, which is then used to perform the transport (phase saturation) computations. To alleviate this computational bottleneck, we replace MCS with a deterministic equation for the cumulative distribution function (CDF) of travel time. The resulting CDF‐FROST approach yields the CDF of the saturation field without resorting to sampling‐based strategies. Our numerical experiments demonstrate the high accuracy of CDF‐FROST in computing the CDFs of both saturation and travel time. For the same accuracy, it is about 5 and 10 times faster than FROST and MCS, respectively.

Yang, Hyung Jun↗

Revealing spatially heterogeneous relaxation in a model nanocomposite

The detailed nature of spatially heterogeneous dynamics of glycerol-silica nanocomposites is unraveled by combining dielectric spectroscopy with atomistic simulation and statistical mechanical theory. Analysis of the spatial mobility gradient shows no “glassy” layer, but the α-relaxation time near the nanoparticle grows with cooling faster than the α-relaxation time in the bulk and is ∼20 times longer at low temperatures. The interfacial layer thickness increases from ∼1.8 nm at higher temperatures to ∼3.5 nm upon cooling to near bulk T{sub g}. A real space microscopic description of the mobility gradient is constructed by synergistically combining high temperature atomistic simulation with theory. Our analysis suggests that the interfacial slowing down arises mainly due to an increase of the local cage scale barrier for activated hopping induced by enhanced packing and densification near the nanoparticle surface. The theory is employed to predict how local surface densification can be manipulated to control layer dynamics and shear rigidity over a wide temperature range.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

High-resolution 2-D Bragg diffraction reveal heterogeneous domain transformation behavior in a bulk relaxor ferroelectric

In-situ measurement of fine-structure of neutron Bragg diffraction peaks from a relaxor single-crystal using a time-of-flight instrument reveals highly heterogeneous mesoscale domain transformation behavior under applied electric fields. We observed that only 25% of domains undergo reorienta- tion or phase transition contributing to large average strains, while at least 40% remain invariant and exhibit microstrains. Such insights could be central for designing new relaxor materials with better performance and longevity. The current experimental technique can also be applied to resolve com- plex mesoscale phenomena in other functional materials.

36 MATERIALS SCIENCE↗

Heterogeneous Seeding of a Prion Structure by a Generic Amyloid Form of the Fungal Prion-forming Domain HET-s(218-289)

The fungal prion-forming domain HET-s(218–289) forms infectious amyloid fibrils at physiological pH that were shown by solid-state NMR to be assemblies of a two-rung β-solenoid structure. Under acidic conditions, HET-s(218–289) has been shown to form amyloid fibrils that have very low infectivity in vivo, but structural information about these fibrils has been very limited. We show by x-ray fiber diffraction that the HET-s(218–289) fibrils formed under acidic conditions have a stacked β-sheet architecture commonly found in short amyloidogenic peptides and denatured protein aggregates. At physiological pH, stacked β-sheet fibrils nucleate the formation of the infectious β-solenoid prions in a process of heterogeneous seeding, but do so with kinetic profiles distinct from those of spontaneous or homogeneous (seeded with infectious β-solenoid fibrils) fibrillization. Several serial passages of stacked β-sheet-seeded solutions lead to fibrillization kinetics similar to homogeneously seeded solutions. Our results directly show that structural mutation can occur between substantially different amyloid architectures, lending credence to the suggestion that the processes of strain adaptation and crossing species barriers are facilitated by structural mutation.

Wan, William↗

Next Generation Workload Management System For Big Data on Heterogeneous Distributed Computing

The Large Hadron Collider (LHC), operating at the international CERN Laboratory in Geneva, Switzerland, is leading Big Data driven scientific explorations. Experiments at the LHC explore the fundamental nature of matter and the basic forces that shape our universe, and were recently credited for the discovery of a Higgs boson. ATLAS and ALICE are the largest collaborations ever assembled in the sciences and are at the forefront of research at the LHC. To address an unprecedented multi-petabyte data processing challenge, both experiments rely on a heterogeneous distributed computational infrastructure. The ATLAS experiment uses PanDA (Production and Data Analysis) Workload Management System (WMS) for managing the workflow for all data processing on hundreds of data centers. Through PanDA, ATLAS physicists see a single computing facility that enables rapid scientific breakthroughs for the experiment, even though the data centers are physically scattered all over the world. The scale is demonstrated by the following numbers: PanDA manages O(10 2 ) sites, O(10 5 ) cores, O(10 8 ) jobs per year, O(10 3 ) users, and ATLAS data volume is O(10 17 ) bytes. In 2013 we started an ambitious program to expand PanDA to all available computing resources, including opportunistic use of commercial and academic clouds and Leadership Computing Facilities (LCF). The project titled 'Next Generation Workload Management and Analysis System for Big Data' (BigPanDA) is funded by DOE ASCR and HEP. Extending PanDA to clouds and LCF presents new challenges in managing heterogeneity and supporting workflow. The BigPanDA project is underway to setup and tailor PanDA at the Oak Ridge Leadership Computing Facility (OLCF) and at the National Research Center "Kurchatov Institute" together with ALICE distributed computing and ORNL computing professionals. Our approach to integration of HPC platforms at the OLCF and elsewhere is to reuse, as much as possible, existing components of the PanDA system. Finally, we will present our current accomplishments with running the PanDA WMS at OLCF and other supercomputers and demonstrate our ability to use PanDA as a portal independent of the computing facilities infrastructure for High Energy and Nuclear Physics as well as other data-intensive science applications.

97 MATHEMATICS AND COMPUTING↗

Comprehensive Monitoring for Heterogeneous Geographically Distributed Storage

Storage capacity at CMS Tier-1 and Tier-2 sites reached over 100 Petabytes in 2014, and will be substantially increased during Run 2 data taking. The allocation of storage for the individual users analysis data, which is not accounted as a centrally managed storage space, will be increased to up to 40%. For comprehensive tracking and monitoring of the storage utilization across all participating sites, CMS developed a space monitoring system, which provides a central view of the geographically dispersed heterogeneous storage systems. The first prototype was deployed at pilot sites in summer 2014, and has been substantially reworked since then. In this paper we discuss the functionality and our experience of system deployment and operation on the full CMS scale.

Ratnikova, N.↗

Preemptive resource management for dynamically arriving tasks in an oversubscribed heterogeneous computing system

We design resource management heuristics that assign serial tasks to the nodes of a heterogeneous high performance computing (HPC) system. The value of completing these tasks is modeled using monotonically decreasing utility functions that represent the time-varying importance of the task. The value of completing a task is equal to its utility function at the time of its completion. The overall performance of this system is measured using the total utility earned by all tasks during some interval of time. To maximize the performance of such a system where the preemption of tasks is possible, we have designed, analyzed, and compared a set of resource allocation heuristic techniques. We combine two utility-aware heuristics with three different preemption techniques to create six preemption-capable heuristics. We also consider the two utility-aware heuristics without preemption. We use simulation studies to evaluate this set of eight heuristics and compare them with an FCFS heuristic, which is often used in real systems, and random assignments. In general, our set of eight heuristics is able to significantly outperform the comparison heuristics, and the preemption-capable heuristics are able to significantly increase the utility earned compared to the heuristics that do not use preemption. We analyze the performance tradeoffs among the different preemption-capable heuristics under a variety of oversubscribed workload environments.

97 MATHEMATICS AND COMPUTING↗

Tundra landscape heterogeneity, not interannual variability, controls the decadal regional carbon balance in the Western Russian Arctic

Across the Arctic, the net ecosystem carbon (C) balance of tundra ecosystems is highly uncertain due to substantial temporal variability of C fluxes and to landscape heterogeneity. We modeled both carbon dioxide (CO2) and methane (CH4) fluxes for the dominant regional land cover types in a sub-Arctic tundra region in northeast European Russia for the period of 2006-2015 using coupled biogeochemical and permafrost models. Modeled net annual CO2 fluxes ranged from -300 g C m-2 y-1 [net uptake] in a willow fen to 3 g C m-2 y-1 [net source] in dry lichen tundra. Modeled annual CH4 emissions ranged from -0.2 to 22.3 g C m-2 y-1 at a peat plateau site and a willow fen site, respectively. Interannual variability over the decade was relatively small (20-30%) in comparison to variability among the land cover types (120-225%). Using high-resolution land cover classification, the region was a net sink of atmospheric CO2 across most land cover types but a net source of CH4 to the atmosphere due to high emissions from permafrost-free fens. Using a lower-resolution for land cover classification resulted in a 20-65% underestimation of regional CH4 flux and smaller (10%) overestimation of regional CO2 uptake, leading to an overall overestimation of the regional GHG sink by 90% due to the underestimation of wetland extent by 60%. Accurately capturing the relative fraction of uplands versus wetlands was key to determining the net regional C balance but required high (<25-30 m) spatial resolution.

Treat, Claire↗

The Minos Computing Library: Efficient Parallel Programming for Extremely Heterogeneous Systems

Hardware specialization has become the silver bullet to achieve efficient high performance, from Systems-on-Chip systems, where hardware specialization can be ``extreme'', to large-scale HPC systems. As the complexity of the systems increases, so does the complexity of programming such architectures in a portable way. This work introduces the Minos Computing Library (MCL), as system software, programming model, and programming model runtime that facilitate programming extremely heterogeneous systems. MCL supports the execution of several multi-threaded applications within the same compute node, performs asynchronous execution of application tasks, efficiently balances computation across hardware resources, and provides performance portability. We show that code developed on a personal desktop automatically scales up to fully utilize powerful workstations with 8 GPUs and down to power-efficient embedded systems. MCL provides up to 17.5x speedup over OpenCL on NVIDIA DGX-1 systems and up to 1.88x speedup on single-GPU systems. In multi-application workloads, MCL dynamically resource allocation provides up to 2.43x performance improvement over manual, static allocation of computing resources.

Gioiosa, Roberto↗

Performance Evaluation of a Two-Dimensional Flood Model on Heterogeneous High-Performance Computing Architectures

This paper describes the implementation of a two-dimensional hydrodynamic flood model with two different numerical schemes on heterogeneous high-performance computing architectures. Both schemes were able to solve the nonlinear hyperbolic shallow water equations using an explicit upwind first-order approach on finite differences and finite volumes, respectively, and were conducted using MPI and CUDA. Four different test cases were simulated on the Summit supercomputer at Oak Ridge National Laboratory. Both numerical schemes scaled up to 128 nodes (768 GPUs) with a maximum 98.2x speedup of over 1 GPU. The lowest run time for the 10 day Hurricane Harvey event simulation at 5 meter resolution (272 million grid cells) was 50 minutes. GPUDirect communication proved to be more convenient than the standard communication strategy. Both strong and weak scaling are shown.

Sharif, Md Bulbul↗

COHORT: Coordination of Heterogeneous Thermostatically Controlled Loads for Demand Flexibility

Demand flexibility is increasingly important for power grids. Careful coordination of thermostatically controlled loads (TCLs) can modulate energy demand, decrease operating costs, and increase grid resiliency. We propose a novel distributed control framework for the Coordination Of HeterOgeneous Residential Thermostatically controlled loads (COHORT). COHORT is a practical, scalable, and versatile solution that coordinates a population of TCLs to jointly optimize a grid-level objective, while satisfying each TCL’s end-use requirements and operational constraints. To achieve that, we decompose the grid-scale problem into subproblems and coordi- nate their solutions to find the global optimum using the alternating direction method of multipliers (ADMM). The TCLs’ local problems are distributed to and computed in parallel at each TCL, making COHORT highly scalable and privacy-preserving. While each TCL poses combinatorial and non-convex constraints, we characterize these constraints as a convex set through relaxation, thereby making COHORT computationally viable over long planning horizons. After coordination, each TCL is responsible for its own control and tracks the agreed-upon power trajectory with its preferred strategy. In this work, we translate continuous power back to discrete on/off actuation, using pulse width modulation. COHORT is generalizable to a wide range of grid objectives, which we demonstrate through three distinct use cases: generation following, minimizing ramping, and peak load curtailment. In a notable experiment, we validated our approach through a hardware-in-the-loop simulation, including a real-world air conditioner (AC) controlled via a smart thermostat, and simulated instances of ACs modeled after real-world data traces. During the 15-day experimental period, COHORT reduced daily peak loads by an average of 12.5% and maintained comfortable temperatures.

demand response↗

The Shock Dynamics of Heterogeneous YSO Jets: 3D Simulations Meet Multi-epoch Observations

High-resolution observations of young stellar object (YSO) jets show them to be composed of many small-scale knots or clumps. In this paper, we report results of 3D numerical simulations designed to study how such clumps interact and create morphologies and kinematic patterns seen in emission line observations. Our simulations focus on clump scale dynamics by imposing velocity differences between spherical, over-dense regions, which then lead to the formation of bow shocks as faster clumps overtake slower material. We show that much of the spatial structure apparent in emission line images of jets arises from the dynamics and interactions of these bow shocks. Our simulations show a variety of time-dependent features, including bright knots associated with Mach stems where the shocks intersect, a “frothy” emission structure that arises from the presence of the Nonlinear Thin Shell Instability along the surfaces of the bow shocks, and the merging and fragmentation of clumps. Our simulations use a new non-equilibrium cooling method to produce synthetic emission maps in H α and [S ii]. These are directly compared to multi-epoch Hubble Space Telescope observations of Herbig–Haro jets. We find excellent agreement between features seen in the simulations and the observations in terms of both proper motion and morphologies. Thus we conclude that YSO jets may be dominated by heterogeneous structures and that interactions between these structures and the shocks they produce can account for many details of YSO jet evolution.

79 ASTRONOMY AND ASTROPHYSICS↗

Water-Mediated Heterogeneously Catalyzed Reactions

Nature takes advantage of the pervasive presence of water to control many enzymatic reactions by utilizing the unique properties of water, which in turn help regulating reaction rates, selectivity, and rates of mass transfer. Some of the natural phenomena in which water plays the role of solvent, reactant, or byproduct find parallels in industrially relevant reactions catalyzed by synthetic heterogeneous catalysts. Here, we address different mechanistic features of catalytic reactions influenced by water. They include modification of reactant (or product) solubility and rate of mass transport; stabilization of reactants, products, and transition states, both in open and confined spaces; and direct participation in the catalytic phenomenon by remote bond polarization, H-shuttling, or acting as a cocatalyst.

Cooperative catalysis↗