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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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Electrochromic polymer infused plasmonic nanohole array shows heterogeneous forward and backward optical scattering response upon polymer electrical permittivity modulation.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
Molecular and heterogeneous water oxidation catalysts improve the performance of hematite as a photoanode via fundamentally different mechanisms.
Abstract not provided
Shale is a highly heterogeneous material across multiple scales. A typical shale consists of nanometer-scale pores and minerals mixed with macro-scale fractures and particles of varying size. High-resolution imaging is crucial for characterizing the composition and microstructure of this rock. Yet, it is generally not feasible to image a large sample of shale at a high resolution over a large field of view (FOV), thus limiting a full characterization of the microstructure of this material. We present a stochastic framework based on multiple-point statistics that uses high-resolution training images to enhance low-resolution images obtained over a large FOV. Here, we demonstrate the approach using X-ray micro-tomography images of organic-rich Woodford shale obtained at two different resolutions and FOV. Results show that the proposed technique can generate realistic high-resolution images of the microstructure of shale over a large FOV.
This paper presents an innovative approach to producing energy-dense, carbon–neutral liquid ammonia as a means for carrying energy. This approach synergistically integrates microwave reaction chemistry with novel heterogeneous catalysis that decouples dinitrogen activation from high-temperature and high-pressure reactions, altering reaction pathways and increasing ammonia formation rate. Results presented here demonstrate that ammonia synthesis can be conducted at 280 ? and ambient pressure to achieve ~1 mmol ammonia/g cat/h over supported ruthenium catalyst systems utilizing microwave irradiation. It is further shown that adding promoter ions such as potassium, cerium, and barium significantly improves the ammonia production rate over undoped ruthenium-based catalysts. This effect could be attributed to enhanced dielectric loss processes that lead to stronger microwave absorption by the catalyst. Measurement of the equilibrium constant under microwave conditions showed a higher ammonia yield than under thermal equilibrium conditions for both the iron- and ruthenium-based catalysts. Finally, this study also illustrates the advantages of using a variable-frequency microwave reactor for ambient-pressure ammonia synthesis. Mechanistically, investigators believed that the oscillating electric fields of the radiation can couple with adsorbed nitrogen on the surface and accelerate its dissociation. Since dinitrogen dissociation on the surface is rate limiting, this effectively accelerates the reaction.
The presence of faults/ fractures or highly permeable zones in the primary sealing caprock of a CO2 storage reservoir can result in leakage of CO2. Monitoring of leakage requires the capability to detect and resolve the onset, location, and volume of leakage in a systematic and timely manner. Pressure-based monitoring possesses such capabilities. This study demonstrates a basis for monitoring network design based on the characterization of CO2 leakage scenarios through an assessment of the integrity and permeability of the caprock inferred from above zone pressure measurements. Four representative heterogeneous fractured seal types are characterized to demonstrate seal permeability ranging from highly permeable to impermeable. Based on Bayesian classification theory, the probability of each fractured caprock scenario given above zone pressure measurements with measurement error is inferred. The sensitivity to injection rate and caprock thickness is also evaluated and the probability of proper classification is calculated. The time required to distinguish between above zone pressure outcomes and the associated leakage scenarios is also computed.
Abstract not provided