Vapor and healing treatment for CH3NH3PbI3-xClx films toward large-area perovskite solar cells

NASA Astrophysics Data System (ADS)

Gouda, Laxman; Gottesman, Ronen; Tirosh, Shay; Haltzi, Eynav; Hu, Jiangang; Ginsburg, Adam; Keller, David A.; Bouhadana, Yaniv; Zaban, Arie

2016-03-01

Hybrid methyl-ammonium lead trihalide perovskites are promising low-cost materials for use in solar cells and other optoelectronic applications. With a certified photovoltaic conversion efficiency record of 20.1%, scale-up for commercial purposes is already underway. However, preparation of large-area perovskite films remains a challenge, and films of perovskites on large electrodes suffer from non-uniform performance. Thus, production and characterization of the lateral uniformity of large-area films is a crucial step towards scale-up of devices. In this paper, we present a reproducible method for improving the lateral uniformity and performance of large-area perovskite solar cells (32 cm2). The method is based on methyl-ammonium iodide (MAI) vapor treatment as a new step in the sequential deposition of perovskite films. Following the MAI vapor treatment, we used high throughput techniques to map the photovoltaic performance throughout the large-area device. The lateral uniformity and performance of all photovoltaic parameters (Voc, Jsc, Fill Factor, Photo-conversion efficiency) increased, with an overall improved photo-conversion efficiency of ~100% following a vapor treatment at 140 °C. Based on XRD and photoluminescence measurements, We propose that the MAI treatment promotes a ``healing effect'' to the perovskite film which increases the lateral uniformity across the large-area solar cell. Thus, the straightforward MAI vapor treatment is highly beneficial for large scale commercialization of perovskite solar cells, regardless of the specific deposition method.Hybrid methyl-ammonium lead trihalide perovskites are promising low-cost materials for use in solar cells and other optoelectronic applications. With a certified photovoltaic conversion efficiency record of 20.1%, scale-up for commercial purposes is already underway. However, preparation of large-area perovskite films remains a challenge, and films of perovskites on large electrodes suffer from non-uniform performance. Thus, production and characterization of the lateral uniformity of large-area films is a crucial step towards scale-up of devices. In this paper, we present a reproducible method for improving the lateral uniformity and performance of large-area perovskite solar cells (32 cm2). The method is based on methyl-ammonium iodide (MAI) vapor treatment as a new step in the sequential deposition of perovskite films. Following the MAI vapor treatment, we used high throughput techniques to map the photovoltaic performance throughout the large-area device. The lateral uniformity and performance of all photovoltaic parameters (Voc, Jsc, Fill Factor, Photo-conversion efficiency) increased, with an overall improved photo-conversion efficiency of ~100% following a vapor treatment at 140 °C. Based on XRD and photoluminescence measurements, We propose that the MAI treatment promotes a ``healing effect'' to the perovskite film which increases the lateral uniformity across the large-area solar cell. Thus, the straightforward MAI vapor treatment is highly beneficial for large scale commercialization of perovskite solar cells, regardless of the specific deposition method. Electronic supplementary information (ESI) available. See DOI: 10.1039/c5nr08658b

Improving Design Efficiency for Large-Scale Heterogeneous Circuits

NASA Astrophysics Data System (ADS)

Gregerson, Anthony

Despite increases in logic density, many Big Data applications must still be partitioned across multiple computing devices in order to meet their strict performance requirements. Among the most demanding of these applications is high-energy physics (HEP), which uses complex computing systems consisting of thousands of FPGAs and ASICs to process the sensor data created by experiments at particles accelerators such as the Large Hadron Collider (LHC). Designing such computing systems is challenging due to the scale of the systems, the exceptionally high-throughput and low-latency performance constraints that necessitate application-specific hardware implementations, the requirement that algorithms are efficiently partitioned across many devices, and the possible need to update the implemented algorithms during the lifetime of the system. In this work, we describe our research to develop flexible architectures for implementing such large-scale circuits on FPGAs. In particular, this work is motivated by (but not limited in scope to) high-energy physics algorithms for the Compact Muon Solenoid (CMS) experiment at the LHC. To make efficient use of logic resources in multi-FPGA systems, we introduce Multi-Personality Partitioning, a novel form of the graph partitioning problem, and present partitioning algorithms that can significantly improve resource utilization on heterogeneous devices while also reducing inter-chip connections. To reduce the high communication costs of Big Data applications, we also introduce Information-Aware Partitioning, a partitioning method that analyzes the data content of application-specific circuits, characterizes their entropy, and selects circuit partitions that enable efficient compression of data between chips. We employ our information-aware partitioning method to improve the performance of the hardware validation platform for evaluating new algorithms for the CMS experiment. Together, these research efforts help to improve the efficiency and decrease the cost of the developing large-scale, heterogeneous circuits needed to enable large-scale application in high-energy physics and other important areas.

Integration and segregation of large-scale brain networks during short-term task automatization

PubMed Central

Mohr, Holger; Wolfensteller, Uta; Betzel, Richard F.; Mišić, Bratislav; Sporns, Olaf; Richiardi, Jonas; Ruge, Hannes

2016-01-01

The human brain is organized into large-scale functional networks that can flexibly reconfigure their connectivity patterns, supporting both rapid adaptive control and long-term learning processes. However, it has remained unclear how short-term network dynamics support the rapid transformation of instructions into fluent behaviour. Comparing fMRI data of a learning sample (N=70) with a control sample (N=67), we find that increasingly efficient task processing during short-term practice is associated with a reorganization of large-scale network interactions. Practice-related efficiency gains are facilitated by enhanced coupling between the cingulo-opercular network and the dorsal attention network. Simultaneously, short-term task automatization is accompanied by decreasing activation of the fronto-parietal network, indicating a release of high-level cognitive control, and a segregation of the default mode network from task-related networks. These findings suggest that short-term task automatization is enabled by the brain's ability to rapidly reconfigure its large-scale network organization involving complementary integration and segregation processes. PMID:27808095

Economically viable large-scale hydrogen liquefaction

NASA Astrophysics Data System (ADS)

Cardella, U.; Decker, L.; Klein, H.

2017-02-01

The liquid hydrogen demand, particularly driven by clean energy applications, will rise in the near future. As industrial large scale liquefiers will play a major role within the hydrogen supply chain, production capacity will have to increase by a multiple of today’s typical sizes. The main goal is to reduce the total cost of ownership for these plants by increasing energy efficiency with innovative and simple process designs, optimized in capital expenditure. New concepts must ensure a manageable plant complexity and flexible operability. In the phase of process development and selection, a dimensioning of key equipment for large scale liquefiers, such as turbines and compressors as well as heat exchangers, must be performed iteratively to ensure technological feasibility and maturity. Further critical aspects related to hydrogen liquefaction, e.g. fluid properties, ortho-para hydrogen conversion, and coldbox configuration, must be analysed in detail. This paper provides an overview on the approach, challenges and preliminary results in the development of efficient as well as economically viable concepts for large-scale hydrogen liquefaction.

Are large farms more efficient? Tenure security, farm size and farm efficiency: evidence from northeast China

NASA Astrophysics Data System (ADS)

Zhou, Yuepeng; Ma, Xianlei; Shi, Xiaoping

2017-04-01

How to increase production efficiency, guarantee grain security, and increase farmers' income using the limited farmland is a great challenge that China is facing. Although theory predicts that secure property rights and moderate scale management of farmland can increase land productivity, reduce farm-related costs, and raise farmer's income, empirical studies on the size and magnitude of these effects are scarce. A number of studies have examined the impacts of land tenure or farm size on productivity or efficiency, respectively. There are also a few studies linking farm size, land tenure and efficiency together. However, to our best knowledge, there are no studies considering tenure security and farm efficiency together for different farm scales in China. In addition, there is little study analyzing the profit frontier. In this study, we particularly focus on the impacts of land tenure security and farm size on farm profit efficiency, using farm level data collected from 23 villages, 811 households in Liaoning in 2015. 7 different farm scales have been identified to further represent small farms, median farms, moderate-scale farms, and large farms. Technical efficiency is analyzed with stochastic frontier production function. The profit efficiency is regressed on a set of explanatory variables which includes farm size dummies, land tenure security indexes, and household characteristics. We found that: 1) The technical efficiency scores for production efficiency (average score = 0.998) indicate that it is already very close to the production frontier, and thus there is little room to improve production efficiency. However, there is larger space to raise profit efficiency (average score = 0.768) by investing more on farm size expansion, seed, hired labor, pesticide, and irrigation. 2) Farms between 50-80 mu are most efficient from the viewpoint of profit efficiency. The so-called moderate-scale farms (100-150 mu) according to the governmental guideline show no advantage in efficiency. 3) Formal land certificates and farmer's participation in land rental market are found to be important determinants of the profit efficiency across different scale of farms. 4) Fertilizer use has been excessive in Liaoning and could lead to the decline of crop profit.

Large-scale self-assembly of uniform submicron silver sulfide material driven by precise pressure control

NASA Astrophysics Data System (ADS)

Qi, Juanjuan; Chen, Ke; Zhang, Shuhao; Yang, Yun; Guo, Lin; Yang, Shihe

2017-03-01

The controllable self-assembly of nanosized building blocks into larger specific structures can provide an efficient method of synthesizing novel materials with excellent properties. The self-assembly of nanocrystals by assisted means is becoming an extremely active area of research, because it provides a method of producing large-scale advanced functional materials with potential applications in the areas of energy, electronics, optics, and biologics. In this study, we applied an efficient strategy, namely, the use of ‘pressure control’ to the assembly of silver sulfide (Ag2S) nanospheres with a diameter of approximately 33 nm into large-scale, uniform Ag2S sub-microspheres with a size of about 0.33 μm. More importantly, this strategy realizes the online control of the overall reaction system, including the pressure, reaction time, and temperature, and could also be used to easily fabricate other functional materials on an industrial scale. Moreover, the thermodynamics and kinetics parameters for the thermal decomposition of silver diethyldithiocarbamate (Ag(DDTC)) are also investigated to explore the formation mechanism of the Ag2S nanosized building blocks which can be assembled into uniform sub-micron scale architecture. As a method of producing sub-micron Ag2S particles by means of the pressure-controlled self-assembly of nanoparticles, we foresee this strategy being an efficient and universally applicable option for constructing other new building blocks and assembling novel and large functional micromaterials on an industrial scale.

Roll-to-Roll printed large-area all-polymer solar cells with 5% efficiency based on a low crystallinity conjugated polymer blend

NASA Astrophysics Data System (ADS)

Gu, Xiaodan; Zhou, Yan; Gu, Kevin; Kurosawa, Tadanori; Yan, Hongping; Wang, Cheng; Toney, Micheal; Bao, Zhenan

The challenge of continuous printing in high efficiency large-area organic solar cells is a key limiting factor for their widespread adoption. We present a materials design concept for achieving large-area, solution coated all-polymer bulk heterojunction (BHJ) solar cells with stable phase separation morphology between the donor and acceptor. The key concept lies in inhibiting strong crystallization of donor and acceptor polymers, thus forming intermixed, low crystallinity and mostly amorphous blends. Based on experiments using donors and acceptors with different degree of crystallinity, our results showed that microphase separated donor and acceptor domain sizes are inversely proportional to the crystallinity of the conjugated polymers. This methodology of using low crystallinity donors and acceptors has the added benefit of forming a consistent and robust morphology that is insensitive to different processing conditions, allowing one to easily scale up the printing process from a small scale solution shearing coater to a large-scale continuous roll-to-roll (R2R) printer. We were able to continuously roll-to-roll slot die print large area all-polymer solar cells with power conversion efficiencies of 5%, with combined cell area up to 10 cm2. This is among the highest efficiencies realized with R2R coated active layer organic materials on flexible substrate. DOE BRIDGE sunshot program. Office of Naval Research.

Roll-to-Roll Printed Large-Area All-Polymer Solar Cells with 5% Efficiency Based on a Low Crystallinity Conjugated Polymer Blend

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gu, Xiaodan; Zhou, Yan; Gu, Kevin

The challenge of continuous printing in high-efficiency large-area organic solar cells is a key limiting factor for their widespread adoption. We present a materials design concept for achieving large-area, solution-coated all-polymer bulk heterojunction solar cells with stable phase separation morphology between the donor and acceptor. The key concept lies in inhibiting strong crystallization of donor and acceptor polymers, thus forming intermixed, low crystallinity, and mostly amorphous blends. Based on experiments using donors and acceptors with different degree of crystallinity, the results show that microphase separated donor and acceptor domain sizes are inversely proportional to the crystallinity of the conjugated polymers.more » This particular methodology of using low crystallinity donors and acceptors has the added benefit of forming a consistent and robust morphology that is insensitive to different processing conditions, allowing one to easily scale up the printing process from a small-scale solution shearing coater to a large-scale continuous roll-to-roll (R2R) printer. Large-area all-polymer solar cells are continuously roll-to-roll slot die printed with power conversion efficiencies of 5%, with combined cell area up to 10 cm 2. This is among the highest efficiencies realized with R2R-coated active layer organic materials on flexible substrate.« less

Roll-to-Roll Printed Large-Area All-Polymer Solar Cells with 5% Efficiency Based on a Low Crystallinity Conjugated Polymer Blend

DOE PAGES

Gu, Xiaodan; Zhou, Yan; Gu, Kevin; ...

2017-03-07

The challenge of continuous printing in high-efficiency large-area organic solar cells is a key limiting factor for their widespread adoption. We present a materials design concept for achieving large-area, solution-coated all-polymer bulk heterojunction solar cells with stable phase separation morphology between the donor and acceptor. The key concept lies in inhibiting strong crystallization of donor and acceptor polymers, thus forming intermixed, low crystallinity, and mostly amorphous blends. Based on experiments using donors and acceptors with different degree of crystallinity, the results show that microphase separated donor and acceptor domain sizes are inversely proportional to the crystallinity of the conjugated polymers.more » This particular methodology of using low crystallinity donors and acceptors has the added benefit of forming a consistent and robust morphology that is insensitive to different processing conditions, allowing one to easily scale up the printing process from a small-scale solution shearing coater to a large-scale continuous roll-to-roll (R2R) printer. Large-area all-polymer solar cells are continuously roll-to-roll slot die printed with power conversion efficiencies of 5%, with combined cell area up to 10 cm 2. This is among the highest efficiencies realized with R2R-coated active layer organic materials on flexible substrate.« less

Adjoint-Based Aerodynamic Design of Complex Aerospace Configurations

NASA Technical Reports Server (NTRS)

Nielsen, Eric J.

2016-01-01

An overview of twenty years of adjoint-based aerodynamic design research at NASA Langley Research Center is presented. Adjoint-based algorithms provide a powerful tool for efficient sensitivity analysis of complex large-scale computational fluid dynamics (CFD) simulations. Unlike alternative approaches for which computational expense generally scales with the number of design parameters, adjoint techniques yield sensitivity derivatives of a simulation output with respect to all input parameters at the cost of a single additional simulation. With modern large-scale CFD applications often requiring millions of compute hours for a single analysis, the efficiency afforded by adjoint methods is critical in realizing a computationally tractable design optimization capability for such applications.

A low-cost iron-cadmium redox flow battery for large-scale energy storage

NASA Astrophysics Data System (ADS)

Zeng, Y. K.; Zhao, T. S.; Zhou, X. L.; Wei, L.; Jiang, H. R.

2016-10-01

The redox flow battery (RFB) is one of the most promising large-scale energy storage technologies that offer a potential solution to the intermittency of renewable sources such as wind and solar. The prerequisite for widespread utilization of RFBs is low capital cost. In this work, an iron-cadmium redox flow battery (Fe/Cd RFB) with a premixed iron and cadmium solution is developed and tested. It is demonstrated that the coulombic efficiency and energy efficiency of the Fe/Cd RFB reach 98.7% and 80.2% at 120 mA cm-2, respectively. The Fe/Cd RFB exhibits stable efficiencies with capacity retention of 99.87% per cycle during the cycle test. Moreover, the Fe/Cd RFB is estimated to have a low capital cost of 108 kWh-1 for 8-h energy storage. Intrinsically low-cost active materials, high cell performance and excellent capacity retention equip the Fe/Cd RFB to be a promising solution for large-scale energy storage systems.

A Computationally Efficient Parallel Levenberg-Marquardt Algorithm for Large-Scale Big-Data Inversion

NASA Astrophysics Data System (ADS)

Lin, Y.; O'Malley, D.; Vesselinov, V. V.

2015-12-01

Inverse modeling seeks model parameters given a set of observed state variables. However, for many practical problems due to the facts that the observed data sets are often large and model parameters are often numerous, conventional methods for solving the inverse modeling can be computationally expensive. We have developed a new, computationally-efficient Levenberg-Marquardt method for solving large-scale inverse modeling. Levenberg-Marquardt methods require the solution of a dense linear system of equations which can be prohibitively expensive to compute for large-scale inverse problems. Our novel method projects the original large-scale linear problem down to a Krylov subspace, such that the dimensionality of the measurements can be significantly reduced. Furthermore, instead of solving the linear system for every Levenberg-Marquardt damping parameter, we store the Krylov subspace computed when solving the first damping parameter and recycle it for all the following damping parameters. The efficiency of our new inverse modeling algorithm is significantly improved by using these computational techniques. We apply this new inverse modeling method to invert for a random transitivity field. Our algorithm is fast enough to solve for the distributed model parameters (transitivity) at each computational node in the model domain. The inversion is also aided by the use regularization techniques. The algorithm is coded in Julia and implemented in the MADS computational framework (http://mads.lanl.gov). Julia is an advanced high-level scientific programing language that allows for efficient memory management and utilization of high-performance computational resources. By comparing with a Levenberg-Marquardt method using standard linear inversion techniques, our Levenberg-Marquardt method yields speed-up ratio of 15 in a multi-core computational environment and a speed-up ratio of 45 in a single-core computational environment. Therefore, our new inverse modeling method is a powerful tool for large-scale applications.

Cross-scale interactions affect tree growth and intrinsic water use efficiency and highlight the importance of spatial context in managing forests under global change

Treesearch

Kenneth J. Ruzicka; Klaus J. Puettmann; J. Renée Brooks

2017-01-01

Summary1. We investigated the potential of cross-scale interactions to affect the outcome of density reduction in a large-scale silvicultural experiment to better understand options for managing forests under climate change. 2. We measured tree growth and intrinsic water-use efficiency (iWUE) based on stable carbon isotopes (δ...

Large-scale Cortical Network Properties Predict Future Sound-to-Word Learning Success

PubMed Central

Sheppard, John Patrick; Wang, Ji-Ping; Wong, Patrick C. M.

2013-01-01

The human brain possesses a remarkable capacity to interpret and recall novel sounds as spoken language. These linguistic abilities arise from complex processing spanning a widely distributed cortical network and are characterized by marked individual variation. Recently, graph theoretical analysis has facilitated the exploration of how such aspects of large-scale brain functional organization may underlie cognitive performance. Brain functional networks are known to possess small-world topologies characterized by efficient global and local information transfer, but whether these properties relate to language learning abilities remains unknown. Here we applied graph theory to construct large-scale cortical functional networks from cerebral hemodynamic (fMRI) responses acquired during an auditory pitch discrimination task and found that such network properties were associated with participants’ future success in learning words of an artificial spoken language. Successful learners possessed networks with reduced local efficiency but increased global efficiency relative to less successful learners and had a more cost-efficient network organization. Regionally, successful and less successful learners exhibited differences in these network properties spanning bilateral prefrontal, parietal, and right temporal cortex, overlapping a core network of auditory language areas. These results suggest that efficient cortical network organization is associated with sound-to-word learning abilities among healthy, younger adults. PMID:22360625

A large-scale photonic node architecture that utilizes interconnected OXC subsystems.

PubMed

Iwai, Yuto; Hasegawa, Hiroshi; Sato, Ken-ichi

2013-01-14

We propose a novel photonic node architecture that is composed of interconnected small-scale optical cross-connect subsystems. We also developed an efficient dynamic network control algorithm that complies with a restriction on the number of intra-node fibers used for subsystem interconnection. Numerical evaluations verify that the proposed architecture offers almost the same performance as the equivalent single large-scale cross-connect switch, while enabling substantial hardware scale reductions.

Efficient parallelization of analytic bond-order potentials for large-scale atomistic simulations

NASA Astrophysics Data System (ADS)

Teijeiro, C.; Hammerschmidt, T.; Drautz, R.; Sutmann, G.

2016-07-01

Analytic bond-order potentials (BOPs) provide a way to compute atomistic properties with controllable accuracy. For large-scale computations of heterogeneous compounds at the atomistic level, both the computational efficiency and memory demand of BOP implementations have to be optimized. Since the evaluation of BOPs is a local operation within a finite environment, the parallelization concepts known from short-range interacting particle simulations can be applied to improve the performance of these simulations. In this work, several efficient parallelization methods for BOPs that use three-dimensional domain decomposition schemes are described. The schemes are implemented into the bond-order potential code BOPfox, and their performance is measured in a series of benchmarks. Systems of up to several millions of atoms are simulated on a high performance computing system, and parallel scaling is demonstrated for up to thousands of processors.

Design of Availability-Dependent Distributed Services in Large-Scale Uncooperative Settings

ERIC Educational Resources Information Center

Morales, Ramses Victor

2009-01-01

Thesis Statement: "Availability-dependent global predicates can be efficiently and scalably realized for a class of distributed services, in spite of specific selfish and colluding behaviors, using local and decentralized protocols". Several types of large-scale distributed systems spanning the Internet have to deal with availability variations…

Sensitivity analysis for large-scale problems

NASA Technical Reports Server (NTRS)

Noor, Ahmed K.; Whitworth, Sandra L.

1987-01-01

The development of efficient techniques for calculating sensitivity derivatives is studied. The objective is to present a computational procedure for calculating sensitivity derivatives as part of performing structural reanalysis for large-scale problems. The scope is limited to framed type structures. Both linear static analysis and free-vibration eigenvalue problems are considered.

Science Competencies That Go Unassessed

ERIC Educational Resources Information Center

Gilmer, Penny J.; Sherdan, Danielle M.; Oosterhof, Albert; Rohani, Faranak; Rouby, Aaron

2011-01-01

Present large-scale assessments require the use of item formats, such as multiple choice, that can be administered and scored efficiently. This limits competencies that can be measured by these assessments. An alternative approach to large-scale assessments is being investigated that would include the use of complex performance assessments. As…

A Discrete Constraint for Entropy Conservation and Sound Waves in Cloud-Resolving Modeling

NASA Technical Reports Server (NTRS)

Zeng, Xi-Ping; Tao, Wei-Kuo; Simpson, Joanne

2003-01-01

Ideal cloud-resolving models contain little-accumulative errors. When their domain is so large that synoptic large-scale circulations are accommodated, they can be used for the simulation of the interaction between convective clouds and the large-scale circulations. This paper sets up a framework for the models, using moist entropy as a prognostic variable and employing conservative numerical schemes. The models possess no accumulative errors of thermodynamic variables when they comply with a discrete constraint on entropy conservation and sound waves. Alternatively speaking, the discrete constraint is related to the correct representation of the large-scale convergence and advection of moist entropy. Since air density is involved in entropy conservation and sound waves, the challenge is how to compute sound waves efficiently under the constraint. To address the challenge, a compensation method is introduced on the basis of a reference isothermal atmosphere whose governing equations are solved analytically. Stability analysis and numerical experiments show that the method allows the models to integrate efficiently with a large time step.

An efficient implementation of 3D high-resolution imaging for large-scale seismic data with GPU/CPU heterogeneous parallel computing

NASA Astrophysics Data System (ADS)

Xu, Jincheng; Liu, Wei; Wang, Jin; Liu, Linong; Zhang, Jianfeng

2018-02-01

De-absorption pre-stack time migration (QPSTM) compensates for the absorption and dispersion of seismic waves by introducing an effective Q parameter, thereby making it an effective tool for 3D, high-resolution imaging of seismic data. Although the optimal aperture obtained via stationary-phase migration reduces the computational cost of 3D QPSTM and yields 3D stationary-phase QPSTM, the associated computational efficiency is still the main problem in the processing of 3D, high-resolution images for real large-scale seismic data. In the current paper, we proposed a division method for large-scale, 3D seismic data to optimize the performance of stationary-phase QPSTM on clusters of graphics processing units (GPU). Then, we designed an imaging point parallel strategy to achieve an optimal parallel computing performance. Afterward, we adopted an asynchronous double buffering scheme for multi-stream to perform the GPU/CPU parallel computing. Moreover, several key optimization strategies of computation and storage based on the compute unified device architecture (CUDA) were adopted to accelerate the 3D stationary-phase QPSTM algorithm. Compared with the initial GPU code, the implementation of the key optimization steps, including thread optimization, shared memory optimization, register optimization and special function units (SFU), greatly improved the efficiency. A numerical example employing real large-scale, 3D seismic data showed that our scheme is nearly 80 times faster than the CPU-QPSTM algorithm. Our GPU/CPU heterogeneous parallel computing framework significant reduces the computational cost and facilitates 3D high-resolution imaging for large-scale seismic data.

The Theory about CD-CAT Based on FCA and Its Application

ERIC Educational Resources Information Center

Shuqun, Yang; Shuliang, Ding; Zhiqiang, Yao

2009-01-01

Cognitive diagnosis (CD) plays an important role in intelligent tutoring system. Computerized adaptive testing (CAT) is adaptive, fair, and efficient, which is suitable to large-scale examination. Traditional cognitive diagnostic test needs quite large number of items, the efficient and tailored CAT could be a remedy for it, so the CAT with…

LARGE-SCALE HYDROGEN PRODUCTION FROM NUCLEAR ENERGY USING HIGH TEMPERATURE ELECTROLYSIS

DOE Office of Scientific and Technical Information (OSTI.GOV)

James E. O'Brien

2010-08-01

Hydrogen can be produced from water splitting with relatively high efficiency using high-temperature electrolysis. This technology makes use of solid-oxide cells, running in the electrolysis mode to produce hydrogen from steam, while consuming electricity and high-temperature process heat. When coupled to an advanced high temperature nuclear reactor, the overall thermal-to-hydrogen efficiency for high-temperature electrolysis can be as high as 50%, which is about double the overall efficiency of conventional low-temperature electrolysis. Current large-scale hydrogen production is based almost exclusively on steam reforming of methane, a method that consumes a precious fossil fuel while emitting carbon dioxide to the atmosphere. Demandmore » for hydrogen is increasing rapidly for refining of increasingly low-grade petroleum resources, such as the Athabasca oil sands and for ammonia-based fertilizer production. Large quantities of hydrogen are also required for carbon-efficient conversion of biomass to liquid fuels. With supplemental nuclear hydrogen, almost all of the carbon in the biomass can be converted to liquid fuels in a nearly carbon-neutral fashion. Ultimately, hydrogen may be employed as a direct transportation fuel in a “hydrogen economy.” The large quantity of hydrogen that would be required for this concept should be produced without consuming fossil fuels or emitting greenhouse gases. An overview of the high-temperature electrolysis technology will be presented, including basic theory, modeling, and experimental activities. Modeling activities include both computational fluid dynamics and large-scale systems analysis. We have also demonstrated high-temperature electrolysis in our laboratory at the 15 kW scale, achieving a hydrogen production rate in excess of 5500 L/hr.« less

Large-scale magnetic fields at high Reynolds numbers in magnetohydrodynamic simulations.

PubMed

Hotta, H; Rempel, M; Yokoyama, T

2016-03-25

The 11-year solar magnetic cycle shows a high degree of coherence in spite of the turbulent nature of the solar convection zone. It has been found in recent high-resolution magnetohydrodynamics simulations that the maintenance of a large-scale coherent magnetic field is difficult with small viscosity and magnetic diffusivity (≲10 (12) square centimenters per second). We reproduced previous findings that indicate a reduction of the energy in the large-scale magnetic field for lower diffusivities and demonstrate the recovery of the global-scale magnetic field using unprecedentedly high resolution. We found an efficient small-scale dynamo that suppresses small-scale flows, which mimics the properties of large diffusivity. As a result, the global-scale magnetic field is maintained even in the regime of small diffusivities-that is, large Reynolds numbers. Copyright © 2016, American Association for the Advancement of Science.

Scaling of the Urban Water Footprint: An Analysis of 65 Mid- to Large-Sized U.S. Metropolitan Areas

NASA Astrophysics Data System (ADS)

Mahjabin, T.; Garcia, S.; Grady, C.; Mejia, A.

2017-12-01

Scaling laws have been shown to be relevant to a range of disciplines including biology, ecology, hydrology, and physics, among others. Recently, scaling was shown to be important for understanding and characterizing cities. For instance, it was found that urban infrastructure (water supply pipes and electrical wires) tends to scale sublinearly with city population, implying that large cities are more efficient. In this study, we explore the scaling of the water footprint of cities. The water footprint is a measure of water appropriation that considers both the direct and indirect (virtual) water use of a consumer or producer. Here we compute the water footprint of 65 mid- to large-sized U.S. metropolitan areas, accounting for direct and indirect water uses associated with agricultural and industrial commodities, and residential and commercial water uses. We find that the urban water footprint, computed as the sum of the water footprint of consumption and production, exhibits sublinear scaling with an exponent of 0.89. This suggests the possibility of large cities being more water-efficient than small ones. To further assess this result, we conduct additional analysis by accounting for international flows, and the effects of green water and city boundary definition on the scaling. The analysis confirms the scaling and provides additional insight about its interpretation.

Large-Scale medical image analytics: Recent methodologies, applications and Future directions.

PubMed

Zhang, Shaoting; Metaxas, Dimitris

2016-10-01

Despite the ever-increasing amount and complexity of annotated medical image data, the development of large-scale medical image analysis algorithms has not kept pace with the need for methods that bridge the semantic gap between images and diagnoses. The goal of this position paper is to discuss and explore innovative and large-scale data science techniques in medical image analytics, which will benefit clinical decision-making and facilitate efficient medical data management. Particularly, we advocate that the scale of image retrieval systems should be significantly increased at which interactive systems can be effective for knowledge discovery in potentially large databases of medical images. For clinical relevance, such systems should return results in real-time, incorporate expert feedback, and be able to cope with the size, quality, and variety of the medical images and their associated metadata for a particular domain. The design, development, and testing of the such framework can significantly impact interactive mining in medical image databases that are growing rapidly in size and complexity and enable novel methods of analysis at much larger scales in an efficient, integrated fashion. Copyright © 2016. Published by Elsevier B.V.

Phase-relationships between scales in the perturbed turbulent boundary layer

NASA Astrophysics Data System (ADS)

Jacobi, I.; McKeon, B. J.

2017-12-01

The phase-relationship between large-scale motions and small-scale fluctuations in a non-equilibrium turbulent boundary layer was investigated. A zero-pressure-gradient flat plate turbulent boundary layer was perturbed by a short array of two-dimensional roughness elements, both statically, and under dynamic actuation. Within the compound, dynamic perturbation, the forcing generated a synthetic very-large-scale motion (VLSM) within the flow. The flow was decomposed by phase-locking the flow measurements to the roughness forcing, and the phase-relationship between the synthetic VLSM and remaining fluctuating scales was explored by correlation techniques. The general relationship between large- and small-scale motions in the perturbed flow, without phase-locking, was also examined. The synthetic large scale cohered with smaller scales in the flow via a phase-relationship that is similar to that of natural large scales in an unperturbed flow, but with a much stronger organizing effect. Cospectral techniques were employed to describe the physical implications of the perturbation on the relative orientation of large- and small-scale structures in the flow. The correlation and cospectral techniques provide tools for designing more efficient control strategies that can indirectly control small-scale motions via the large scales.

Very Large Scale Aerial (VLSA) imagery for assessing postfire bitterbrush recovery

Treesearch

Corey A. Moffet; J. Bret Taylor; D. Terrance Booth

2008-01-01

Very large scale aerial (VLSA) imagery is an efficient tool for monitoring bare ground and cover on extensive rangelands. This study was conducted to determine whether VLSA images could be used to detect differences in antelope bitterbrush (Purshia tridentata Pursh DC) cover and density among similar ecological sites with varying postfire recovery...

Novel patch modelling method for efficient simulation and prediction uncertainty analysis of multi-scale groundwater flow and transport processes

NASA Astrophysics Data System (ADS)

Sreekanth, J.; Moore, Catherine

2018-04-01

The application of global sensitivity and uncertainty analysis techniques to groundwater models of deep sedimentary basins are typically challenged by large computational burdens combined with associated numerical stability issues. The highly parameterized approaches required for exploring the predictive uncertainty associated with the heterogeneous hydraulic characteristics of multiple aquifers and aquitards in these sedimentary basins exacerbate these issues. A novel Patch Modelling Methodology is proposed for improving the computational feasibility of stochastic modelling analysis of large-scale and complex groundwater models. The method incorporates a nested groundwater modelling framework that enables efficient simulation of groundwater flow and transport across multiple spatial and temporal scales. The method also allows different processes to be simulated within different model scales. Existing nested model methodologies are extended by employing 'joining predictions' for extrapolating prediction-salient information from one model scale to the next. This establishes a feedback mechanism supporting the transfer of information from child models to parent models as well as parent models to child models in a computationally efficient manner. This feedback mechanism is simple and flexible and ensures that while the salient small scale features influencing larger scale prediction are transferred back to the larger scale, this does not require the live coupling of models. This method allows the modelling of multiple groundwater flow and transport processes using separate groundwater models that are built for the appropriate spatial and temporal scales, within a stochastic framework, while also removing the computational burden associated with live model coupling. The utility of the method is demonstrated by application to an actual large scale aquifer injection scheme in Australia.

Sparse deconvolution for the large-scale ill-posed inverse problem of impact force reconstruction

NASA Astrophysics Data System (ADS)

Qiao, Baijie; Zhang, Xingwu; Gao, Jiawei; Liu, Ruonan; Chen, Xuefeng

2017-01-01

Most previous regularization methods for solving the inverse problem of force reconstruction are to minimize the l2-norm of the desired force. However, these traditional regularization methods such as Tikhonov regularization and truncated singular value decomposition, commonly fail to solve the large-scale ill-posed inverse problem in moderate computational cost. In this paper, taking into account the sparse characteristic of impact force, the idea of sparse deconvolution is first introduced to the field of impact force reconstruction and a general sparse deconvolution model of impact force is constructed. Second, a novel impact force reconstruction method based on the primal-dual interior point method (PDIPM) is proposed to solve such a large-scale sparse deconvolution model, where minimizing the l2-norm is replaced by minimizing the l1-norm. Meanwhile, the preconditioned conjugate gradient algorithm is used to compute the search direction of PDIPM with high computational efficiency. Finally, two experiments including the small-scale or medium-scale single impact force reconstruction and the relatively large-scale consecutive impact force reconstruction are conducted on a composite wind turbine blade and a shell structure to illustrate the advantage of PDIPM. Compared with Tikhonov regularization, PDIPM is more efficient, accurate and robust whether in the single impact force reconstruction or in the consecutive impact force reconstruction.

paraGSEA: a scalable approach for large-scale gene expression profiling

PubMed Central

Peng, Shaoliang; Yang, Shunyun

2017-01-01

Abstract More studies have been conducted using gene expression similarity to identify functional connections among genes, diseases and drugs. Gene Set Enrichment Analysis (GSEA) is a powerful analytical method for interpreting gene expression data. However, due to its enormous computational overhead in the estimation of significance level step and multiple hypothesis testing step, the computation scalability and efficiency are poor on large-scale datasets. We proposed paraGSEA for efficient large-scale transcriptome data analysis. By optimization, the overall time complexity of paraGSEA is reduced from O(mn) to O(m+n), where m is the length of the gene sets and n is the length of the gene expression profiles, which contributes more than 100-fold increase in performance compared with other popular GSEA implementations such as GSEA-P, SAM-GS and GSEA2. By further parallelization, a near-linear speed-up is gained on both workstations and clusters in an efficient manner with high scalability and performance on large-scale datasets. The analysis time of whole LINCS phase I dataset (GSE92742) was reduced to nearly half hour on a 1000 node cluster on Tianhe-2, or within 120 hours on a 96-core workstation. The source code of paraGSEA is licensed under the GPLv3 and available at http://github.com/ysycloud/paraGSEA. PMID:28973463

Large-scale two-photon imaging revealed super-sparse population codes in the V1 superficial layer of awake monkeys.

PubMed

Tang, Shiming; Zhang, Yimeng; Li, Zhihao; Li, Ming; Liu, Fang; Jiang, Hongfei; Lee, Tai Sing

2018-04-26

One general principle of sensory information processing is that the brain must optimize efficiency by reducing the number of neurons that process the same information. The sparseness of the sensory representations in a population of neurons reflects the efficiency of the neural code. Here, we employ large-scale two-photon calcium imaging to examine the responses of a large population of neurons within the superficial layers of area V1 with single-cell resolution, while simultaneously presenting a large set of natural visual stimuli, to provide the first direct measure of the population sparseness in awake primates. The results show that only 0.5% of neurons respond strongly to any given natural image - indicating a ten-fold increase in the inferred sparseness over previous measurements. These population activities are nevertheless necessary and sufficient to discriminate visual stimuli with high accuracy, suggesting that the neural code in the primary visual cortex is both super-sparse and highly efficient. © 2018, Tang et al.

Efficient Computation of Sparse Matrix Functions for Large-Scale Electronic Structure Calculations: The CheSS Library.

PubMed

Mohr, Stephan; Dawson, William; Wagner, Michael; Caliste, Damien; Nakajima, Takahito; Genovese, Luigi

2017-10-10

We present CheSS, the "Chebyshev Sparse Solvers" library, which has been designed to solve typical problems arising in large-scale electronic structure calculations using localized basis sets. The library is based on a flexible and efficient expansion in terms of Chebyshev polynomials and presently features the calculation of the density matrix, the calculation of matrix powers for arbitrary powers, and the extraction of eigenvalues in a selected interval. CheSS is able to exploit the sparsity of the matrices and scales linearly with respect to the number of nonzero entries, making it well-suited for large-scale calculations. The approach is particularly adapted for setups leading to small spectral widths of the involved matrices and outperforms alternative methods in this regime. By coupling CheSS to the DFT code BigDFT, we show that such a favorable setup is indeed possible in practice. In addition, the approach based on Chebyshev polynomials can be massively parallelized, and CheSS exhibits excellent scaling up to thousands of cores even for relatively small matrix sizes.

Solar Trees: First Large-Scale Demonstration of Fully Solution Coated, Semitransparent, Flexible Organic Photovoltaic Modules.

PubMed

Berny, Stephane; Blouin, Nicolas; Distler, Andreas; Egelhaaf, Hans-Joachim; Krompiec, Michal; Lohr, Andreas; Lozman, Owen R; Morse, Graham E; Nanson, Lana; Pron, Agnieszka; Sauermann, Tobias; Seidler, Nico; Tierney, Steve; Tiwana, Priti; Wagner, Michael; Wilson, Henry

2016-05-01

The technology behind a large area array of flexible solar cells with a unique design and semitransparent blue appearance is presented. These modules are implemented in a solar tree installation at the German pavilion in the EXPO2015 in Milan/IT. The modules show power conversion efficiencies of 4.5% and are produced exclusively using standard printing techniques for large-scale production.

Research on the self-absorption corrections for PGNAA of large samples

NASA Astrophysics Data System (ADS)

Yang, Jian-Bo; Liu, Zhi; Chang, Kang; Li, Rui

2017-02-01

When a large sample is analysed with the prompt gamma neutron activation analysis (PGNAA) neutron self-shielding and gamma self-absorption affect the accuracy, the correction method for the detection efficiency of the relative H of each element in a large sample is described. The influences of the thickness and density of the cement samples on the H detection efficiency, as well as the impurities Fe2O3 and SiO2 on the prompt γ ray yield for each element in the cement samples, were studied. The phase functions for Ca, Fe, and Si on H with changes in sample thickness and density were provided to avoid complicated procedures for preparing the corresponding density or thickness scale for measuring samples under each density or thickness value and to present a simplified method for the measurement efficiency scale for prompt-gamma neutron activation analysis.

Los Alamos Discovers Super Efficient Solar Using Perovskite Crystals

ScienceCinema

Mohite, Aditya; Nie, Wanyi

2018-05-11

State-of-the-art photovoltaics using high-purity, large-area, wafer-scale single-crystalline semiconductors grown by sophisticated, high temperature crystal-growth processes offer promising routes for developing low-cost, solar-based clean global energy solutions for the future. Solar cells composed of the recently discovered material organic-inorganic perovskites offer the efficiency of silicon, yet suffer from a variety of deficiencies limiting the commercial viability of perovskite photovoltaic technology. In research to appear in Science, Los Alamos National Laboratory researchers reveal a new solution-based hot-casting technique that eliminates these limitations, one that allows for the growth of high-quality, large-area, millimeter-scale perovskite crystals and demonstrates that highly efficient and reproducible solar cells with reduced trap assisted recombination can be realized.

Large-scale block adjustment without use of ground control points based on the compensation of geometric calibration for ZY-3 images

NASA Astrophysics Data System (ADS)

Yang, Bo; Wang, Mi; Xu, Wen; Li, Deren; Gong, Jianya; Pi, Yingdong

2017-12-01

The potential of large-scale block adjustment (BA) without ground control points (GCPs) has long been a concern among photogrammetric researchers, which is of effective guiding significance for global mapping. However, significant problems with the accuracy and efficiency of this method remain to be solved. In this study, we analyzed the effects of geometric errors on BA, and then developed a step-wise BA method to conduct integrated processing of large-scale ZY-3 satellite images without GCPs. We first pre-processed the BA data, by adopting a geometric calibration (GC) method based on the viewing-angle model to compensate for systematic errors, such that the BA input images were of good initial geometric quality. The second step was integrated BA without GCPs, in which a series of technical methods were used to solve bottleneck problems and ensure accuracy and efficiency. The BA model, based on virtual control points (VCPs), was constructed to address the rank deficiency problem caused by lack of absolute constraints. We then developed a parallel matching strategy to improve the efficiency of tie points (TPs) matching, and adopted a three-array data structure based on sparsity to relieve the storage and calculation burden of the high-order modified equation. Finally, we used the conjugate gradient method to improve the speed of solving the high-order equations. To evaluate the feasibility of the presented large-scale BA method, we conducted three experiments on real data collected by the ZY-3 satellite. The experimental results indicate that the presented method can effectively improve the geometric accuracies of ZY-3 satellite images. This study demonstrates the feasibility of large-scale mapping without GCPs.

Multi-thread parallel algorithm for reconstructing 3D large-scale porous structures

NASA Astrophysics Data System (ADS)

Ju, Yang; Huang, Yaohui; Zheng, Jiangtao; Qian, Xu; Xie, Heping; Zhao, Xi

2017-04-01

Geomaterials inherently contain many discontinuous, multi-scale, geometrically irregular pores, forming a complex porous structure that governs their mechanical and transport properties. The development of an efficient reconstruction method for representing porous structures can significantly contribute toward providing a better understanding of the governing effects of porous structures on the properties of porous materials. In order to improve the efficiency of reconstructing large-scale porous structures, a multi-thread parallel scheme was incorporated into the simulated annealing reconstruction method. In the method, four correlation functions, which include the two-point probability function, the linear-path functions for the pore phase and the solid phase, and the fractal system function for the solid phase, were employed for better reproduction of the complex well-connected porous structures. In addition, a random sphere packing method and a self-developed pre-conditioning method were incorporated to cast the initial reconstructed model and select independent interchanging pairs for parallel multi-thread calculation, respectively. The accuracy of the proposed algorithm was evaluated by examining the similarity between the reconstructed structure and a prototype in terms of their geometrical, topological, and mechanical properties. Comparisons of the reconstruction efficiency of porous models with various scales indicated that the parallel multi-thread scheme significantly shortened the execution time for reconstruction of a large-scale well-connected porous model compared to a sequential single-thread procedure.

Robust large-scale parallel nonlinear solvers for simulations.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bader, Brett William; Pawlowski, Roger Patrick; Kolda, Tamara Gibson

2005-11-01

This report documents research to develop robust and efficient solution techniques for solving large-scale systems of nonlinear equations. The most widely used method for solving systems of nonlinear equations is Newton's method. While much research has been devoted to augmenting Newton-based solvers (usually with globalization techniques), little has been devoted to exploring the application of different models. Our research has been directed at evaluating techniques using different models than Newton's method: a lower order model, Broyden's method, and a higher order model, the tensor method. We have developed large-scale versions of each of these models and have demonstrated their usemore » in important applications at Sandia. Broyden's method replaces the Jacobian with an approximation, allowing codes that cannot evaluate a Jacobian or have an inaccurate Jacobian to converge to a solution. Limited-memory methods, which have been successful in optimization, allow us to extend this approach to large-scale problems. We compare the robustness and efficiency of Newton's method, modified Newton's method, Jacobian-free Newton-Krylov method, and our limited-memory Broyden method. Comparisons are carried out for large-scale applications of fluid flow simulations and electronic circuit simulations. Results show that, in cases where the Jacobian was inaccurate or could not be computed, Broyden's method converged in some cases where Newton's method failed to converge. We identify conditions where Broyden's method can be more efficient than Newton's method. We also present modifications to a large-scale tensor method, originally proposed by Bouaricha, for greater efficiency, better robustness, and wider applicability. Tensor methods are an alternative to Newton-based methods and are based on computing a step based on a local quadratic model rather than a linear model. The advantage of Bouaricha's method is that it can use any existing linear solver, which makes it simple to write and easily portable. However, the method usually takes twice as long to solve as Newton-GMRES on general problems because it solves two linear systems at each iteration. In this paper, we discuss modifications to Bouaricha's method for a practical implementation, including a special globalization technique and other modifications for greater efficiency. We present numerical results showing computational advantages over Newton-GMRES on some realistic problems. We further discuss a new approach for dealing with singular (or ill-conditioned) matrices. In particular, we modify an algorithm for identifying a turning point so that an increasingly ill-conditioned Jacobian does not prevent convergence.« less

Aqueous Two-Phase Systems at Large Scale: Challenges and Opportunities.

PubMed

Torres-Acosta, Mario A; Mayolo-Deloisa, Karla; González-Valdez, José; Rito-Palomares, Marco

2018-06-07

Aqueous two-phase systems (ATPS) have proved to be an efficient and integrative operation to enhance recovery of industrially relevant bioproducts. After ATPS discovery, a variety of works have been published regarding their scaling from 10 to 1000 L. Although ATPS have achieved high recovery and purity yields, there is still a gap between their bench-scale use and potential industrial applications. In this context, this review paper critically analyzes ATPS scale-up strategies to enhance the potential industrial adoption. In particular, large-scale operation considerations, different phase separation procedures, the available optimization techniques (univariate, response surface methodology, and genetic algorithms) to maximize recovery and purity and economic modeling to predict large-scale costs, are discussed. ATPS intensification to increase the amount of sample to process at each system, developing recycling strategies and creating highly efficient predictive models, are still areas of great significance that can be further exploited with the use of high-throughput techniques. Moreover, the development of novel ATPS can maximize their specificity increasing the possibilities for the future industry adoption of ATPS. This review work attempts to present the areas of opportunity to increase ATPS attractiveness at industrial levels. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Enhancing ecosystem restoration efficiency through spatial and temporal coordination.

PubMed

Neeson, Thomas M; Ferris, Michael C; Diebel, Matthew W; Doran, Patrick J; O'Hanley, Jesse R; McIntyre, Peter B

2015-05-12

In many large ecosystems, conservation projects are selected by a diverse set of actors operating independently at spatial scales ranging from local to international. Although small-scale decision making can leverage local expert knowledge, it also may be an inefficient means of achieving large-scale objectives if piecemeal efforts are poorly coordinated. Here, we assess the value of coordinating efforts in both space and time to maximize the restoration of aquatic ecosystem connectivity. Habitat fragmentation is a leading driver of declining biodiversity and ecosystem services in rivers worldwide, and we simultaneously evaluate optimal barrier removal strategies for 661 tributary rivers of the Laurentian Great Lakes, which are fragmented by at least 6,692 dams and 232,068 road crossings. We find that coordinating barrier removals across the entire basin is nine times more efficient at reconnecting fish to headwater breeding grounds than optimizing independently for each watershed. Similarly, a one-time pulse of restoration investment is up to 10 times more efficient than annual allocations totaling the same amount. Despite widespread emphasis on dams as key barriers in river networks, improving road culvert passability is also essential for efficiently restoring connectivity to the Great Lakes. Our results highlight the dramatic economic and ecological advantages of coordinating efforts in both space and time during restoration of large ecosystems.

Enhancing ecosystem restoration efficiency through spatial and temporal coordination

PubMed Central

Neeson, Thomas M.; Ferris, Michael C.; Diebel, Matthew W.; Doran, Patrick J.; O’Hanley, Jesse R.; McIntyre, Peter B.

2015-01-01

In many large ecosystems, conservation projects are selected by a diverse set of actors operating independently at spatial scales ranging from local to international. Although small-scale decision making can leverage local expert knowledge, it also may be an inefficient means of achieving large-scale objectives if piecemeal efforts are poorly coordinated. Here, we assess the value of coordinating efforts in both space and time to maximize the restoration of aquatic ecosystem connectivity. Habitat fragmentation is a leading driver of declining biodiversity and ecosystem services in rivers worldwide, and we simultaneously evaluate optimal barrier removal strategies for 661 tributary rivers of the Laurentian Great Lakes, which are fragmented by at least 6,692 dams and 232,068 road crossings. We find that coordinating barrier removals across the entire basin is nine times more efficient at reconnecting fish to headwater breeding grounds than optimizing independently for each watershed. Similarly, a one-time pulse of restoration investment is up to 10 times more efficient than annual allocations totaling the same amount. Despite widespread emphasis on dams as key barriers in river networks, improving road culvert passability is also essential for efficiently restoring connectivity to the Great Lakes. Our results highlight the dramatic economic and ecological advantages of coordinating efforts in both space and time during restoration of large ecosystems. PMID:25918378

Research of an emergency medical system for mass casualty incidents in Shanghai, China: a system dynamics model.

PubMed

Yu, Wenya; Lv, Yipeng; Hu, Chaoqun; Liu, Xu; Chen, Haiping; Xue, Chen; Zhang, Lulu

2018-01-01

Emergency medical system for mass casualty incidents (EMS-MCIs) is a global issue. However, China lacks such studies extremely, which cannot meet the requirement of rapid decision-support system. This study aims to realize modeling EMS-MCIs in Shanghai, to improve mass casualty incident (MCI) rescue efficiency in China, and to provide a possible method of making rapid rescue decisions during MCIs. This study established a system dynamics (SD) model of EMS-MCIs using the Vensim DSS program. Intervention scenarios were designed as adjusting scales of MCIs, allocation of ambulances, allocation of emergency medical staff, and efficiency of organization and command. Mortality increased with the increasing scale of MCIs, medical rescue capability of hospitals was relatively good, but the efficiency of organization and command was poor, and the prehospital time was too long. Mortality declined significantly when increasing ambulances and improving the efficiency of organization and command; triage and on-site first-aid time were shortened if increasing the availability of emergency medical staff. The effect was the most evident when 2,000 people were involved in MCIs; however, the influence was very small under the scale of 5,000 people. The keys to decrease the mortality of MCIs were shortening the prehospital time and improving the efficiency of organization and command. For small-scale MCIs, improving the utilization rate of health resources was important in decreasing the mortality. For large-scale MCIs, increasing the number of ambulances and emergency medical professionals was the core to decrease prehospital time and mortality. For super-large-scale MCIs, increasing health resources was the premise.

Large Eddy Simulation in the Computation of Jet Noise

NASA Technical Reports Server (NTRS)

Mankbadi, R. R.; Goldstein, M. E.; Povinelli, L. A.; Hayder, M. E.; Turkel, E.

1999-01-01

Noise can be predicted by solving Full (time-dependent) Compressible Navier-Stokes Equation (FCNSE) with computational domain. The fluctuating near field of the jet produces propagating pressure waves that produce far-field sound. The fluctuating flow field as a function of time is needed in order to calculate sound from first principles. Noise can be predicted by solving the full, time-dependent, compressible Navier-Stokes equations with the computational domain extended to far field - but this is not feasible as indicated above. At high Reynolds number of technological interest turbulence has large range of scales. Direct numerical simulations (DNS) can not capture the small scales of turbulence. The large scales are more efficient than the small scales in radiating sound. The emphasize is thus on calculating sound radiated by large scales.

Solutions of large-scale electromagnetics problems involving dielectric objects with the parallel multilevel fast multipole algorithm.

PubMed

Ergül, Özgür

2011-11-01

Fast and accurate solutions of large-scale electromagnetics problems involving homogeneous dielectric objects are considered. Problems are formulated with the electric and magnetic current combined-field integral equation and discretized with the Rao-Wilton-Glisson functions. Solutions are performed iteratively by using the multilevel fast multipole algorithm (MLFMA). For the solution of large-scale problems discretized with millions of unknowns, MLFMA is parallelized on distributed-memory architectures using a rigorous technique, namely, the hierarchical partitioning strategy. Efficiency and accuracy of the developed implementation are demonstrated on very large problems involving as many as 100 million unknowns.

Parallel Domain Decomposition Formulation and Software for Large-Scale Sparse Symmetrical/Unsymmetrical Aeroacoustic Applications

NASA Technical Reports Server (NTRS)

Nguyen, D. T.; Watson, Willie R. (Technical Monitor)

2005-01-01

The overall objectives of this research work are to formulate and validate efficient parallel algorithms, and to efficiently design/implement computer software for solving large-scale acoustic problems, arised from the unified frameworks of the finite element procedures. The adopted parallel Finite Element (FE) Domain Decomposition (DD) procedures should fully take advantages of multiple processing capabilities offered by most modern high performance computing platforms for efficient parallel computation. To achieve this objective. the formulation needs to integrate efficient sparse (and dense) assembly techniques, hybrid (or mixed) direct and iterative equation solvers, proper pre-conditioned strategies, unrolling strategies, and effective processors' communicating schemes. Finally, the numerical performance of the developed parallel finite element procedures will be evaluated by solving series of structural, and acoustic (symmetrical and un-symmetrical) problems (in different computing platforms). Comparisons with existing "commercialized" and/or "public domain" software are also included, whenever possible.

Using the High-Level Based Program Interface to Facilitate the Large Scale Scientific Computing

PubMed Central

Shang, Yizi; Shang, Ling; Gao, Chuanchang; Lu, Guiming; Ye, Yuntao; Jia, Dongdong

2014-01-01

This paper is to make further research on facilitating the large-scale scientific computing on the grid and the desktop grid platform. The related issues include the programming method, the overhead of the high-level program interface based middleware, and the data anticipate migration. The block based Gauss Jordan algorithm as a real example of large-scale scientific computing is used to evaluate those issues presented above. The results show that the high-level based program interface makes the complex scientific applications on large-scale scientific platform easier, though a little overhead is unavoidable. Also, the data anticipation migration mechanism can improve the efficiency of the platform which needs to process big data based scientific applications. PMID:24574931

Supercapacitors specialities - Technology review

NASA Astrophysics Data System (ADS)

Münchgesang, Wolfram; Meisner, Patrick; Yushin, Gleb

2014-06-01

Commercial electrochemical capacitors (supercapacitors) are not limited to mobile electronics anymore, but have reached the field of large-scale applications, like smart grid, wind turbines, power for large scale ground, water and aerial transportation, energy-efficient industrial equipment and others. This review gives a short overview of the current state-of-the-art of electrochemical capacitors, their commercial applications and the impact of technological development on performance.

Measurement repeatability of a large-scale inventory of forest fuels

Treesearch

J.A. Westfall; C.W. Woodall

2007-01-01

An efficient and accurate inventory of forest fuels at large scales is critical for assessment of forest fire hazards across landscapes. The Forest Inventory and Analysis (FIA) program of the USDA Forest Service conducts a national inventory of fuels along with blind remeasurement of a portion of inventory plots to monitor and improve data quality. The goal of this...

Supercapacitors specialities - Technology review

DOE Office of Scientific and Technical Information (OSTI.GOV)

Münchgesang, Wolfram; Meisner, Patrick; Yushin, Gleb

2014-06-16

Commercial electrochemical capacitors (supercapacitors) are not limited to mobile electronics anymore, but have reached the field of large-scale applications, like smart grid, wind turbines, power for large scale ground, water and aerial transportation, energy-efficient industrial equipment and others. This review gives a short overview of the current state-of-the-art of electrochemical capacitors, their commercial applications and the impact of technological development on performance.

Cloud-based bioinformatics workflow platform for large-scale next-generation sequencing analyses

PubMed Central

Liu, Bo; Madduri, Ravi K; Sotomayor, Borja; Chard, Kyle; Lacinski, Lukasz; Dave, Utpal J; Li, Jianqiang; Liu, Chunchen; Foster, Ian T

2014-01-01

Due to the upcoming data deluge of genome data, the need for storing and processing large-scale genome data, easy access to biomedical analyses tools, efficient data sharing and retrieval has presented significant challenges. The variability in data volume results in variable computing and storage requirements, therefore biomedical researchers are pursuing more reliable, dynamic and convenient methods for conducting sequencing analyses. This paper proposes a Cloud-based bioinformatics workflow platform for large-scale next-generation sequencing analyses, which enables reliable and highly scalable execution of sequencing analyses workflows in a fully automated manner. Our platform extends the existing Galaxy workflow system by adding data management capabilities for transferring large quantities of data efficiently and reliably (via Globus Transfer), domain-specific analyses tools preconfigured for immediate use by researchers (via user-specific tools integration), automatic deployment on Cloud for on-demand resource allocation and pay-as-you-go pricing (via Globus Provision), a Cloud provisioning tool for auto-scaling (via HTCondor scheduler), and the support for validating the correctness of workflows (via semantic verification tools). Two bioinformatics workflow use cases as well as performance evaluation are presented to validate the feasibility of the proposed approach. PMID:24462600

Cloud-based bioinformatics workflow platform for large-scale next-generation sequencing analyses.

PubMed

Liu, Bo; Madduri, Ravi K; Sotomayor, Borja; Chard, Kyle; Lacinski, Lukasz; Dave, Utpal J; Li, Jianqiang; Liu, Chunchen; Foster, Ian T

2014-06-01

Due to the upcoming data deluge of genome data, the need for storing and processing large-scale genome data, easy access to biomedical analyses tools, efficient data sharing and retrieval has presented significant challenges. The variability in data volume results in variable computing and storage requirements, therefore biomedical researchers are pursuing more reliable, dynamic and convenient methods for conducting sequencing analyses. This paper proposes a Cloud-based bioinformatics workflow platform for large-scale next-generation sequencing analyses, which enables reliable and highly scalable execution of sequencing analyses workflows in a fully automated manner. Our platform extends the existing Galaxy workflow system by adding data management capabilities for transferring large quantities of data efficiently and reliably (via Globus Transfer), domain-specific analyses tools preconfigured for immediate use by researchers (via user-specific tools integration), automatic deployment on Cloud for on-demand resource allocation and pay-as-you-go pricing (via Globus Provision), a Cloud provisioning tool for auto-scaling (via HTCondor scheduler), and the support for validating the correctness of workflows (via semantic verification tools). Two bioinformatics workflow use cases as well as performance evaluation are presented to validate the feasibility of the proposed approach. Copyright © 2014 Elsevier Inc. All rights reserved.

The application of DEA (Data Envelopment Analysis) window analysis in the assessment of influence on operational efficiencies after the establishment of branched hospitals.

PubMed

Jia, Tongying; Yuan, Huiyun

2017-04-12

Many large-scaled public hospitals have established branched hospitals in China. This study is to provide evidence for strategy making on the management and development of multi-branched hospitals by evaluating and comparing the operational efficiencies of different hospitals before and after their establishment of branched hospitals. DEA (Data Envelopment Analysis) window analysis was performed on a 7-year data pool from five public hospitals provided by health authorities and institutional surveys. The operational efficiencies of sample hospitals measured in this study (including technical efficiency, pure technical efficiency and scale efficiency) had overall trends towards increase during this 7-year period of time, however, a temporary downturn occurred shortly after the establishment of branched hospitals; pure technical efficiency contributed more to the improvement of technical efficiency compared to scale efficiency. The establishment of branched-hospitals did not lead to a long-term negative effect on hospital operational efficiencies. Our data indicated the importance of improving scale efficiency via the optimization of organizational management, as well as the advantage of a different form of branch-establishment, merging and reorganization. This study brought an insight into the practical application of DEA window analysis on the assessment of hospital operational efficiencies.

A Simple Non-equilibrium Model of Star Formation and Scatter in the Kennicutt-Schmidt Relation and Star Formation Efficiencies in Galaxies

NASA Astrophysics Data System (ADS)

Orr, Matthew; Hopkins, Philip F.

2018-06-01

I will present a simple model of non-equilibrium star formation and its relation to the scatter in the Kennicutt-Schmidt relation and large-scale star formation efficiencies in galaxies. I will highlight the importance of a hierarchy of timescales, between the galaxy dynamical time, local free-fall time, the delay time of stellar feedback, and temporal overlap in observables, in setting the scatter of the observed star formation rates for a given gas mass. Further, I will talk about how these timescales (and their associated duty-cycles of star formation) influence interpretations of the large-scale star formation efficiency in reasonably star-forming galaxies. Lastly, the connection with galactic centers and out-of-equilibrium feedback conditions will be mentioned.

Big Data Analytics with Datalog Queries on Spark.

PubMed

Shkapsky, Alexander; Yang, Mohan; Interlandi, Matteo; Chiu, Hsuan; Condie, Tyson; Zaniolo, Carlo

2016-01-01

There is great interest in exploiting the opportunity provided by cloud computing platforms for large-scale analytics. Among these platforms, Apache Spark is growing in popularity for machine learning and graph analytics. Developing efficient complex analytics in Spark requires deep understanding of both the algorithm at hand and the Spark API or subsystem APIs (e.g., Spark SQL, GraphX). Our BigDatalog system addresses the problem by providing concise declarative specification of complex queries amenable to efficient evaluation. Towards this goal, we propose compilation and optimization techniques that tackle the important problem of efficiently supporting recursion in Spark. We perform an experimental comparison with other state-of-the-art large-scale Datalog systems and verify the efficacy of our techniques and effectiveness of Spark in supporting Datalog-based analytics.

Big Data Analytics with Datalog Queries on Spark

PubMed Central

Shkapsky, Alexander; Yang, Mohan; Interlandi, Matteo; Chiu, Hsuan; Condie, Tyson; Zaniolo, Carlo

2017-01-01

There is great interest in exploiting the opportunity provided by cloud computing platforms for large-scale analytics. Among these platforms, Apache Spark is growing in popularity for machine learning and graph analytics. Developing efficient complex analytics in Spark requires deep understanding of both the algorithm at hand and the Spark API or subsystem APIs (e.g., Spark SQL, GraphX). Our BigDatalog system addresses the problem by providing concise declarative specification of complex queries amenable to efficient evaluation. Towards this goal, we propose compilation and optimization techniques that tackle the important problem of efficiently supporting recursion in Spark. We perform an experimental comparison with other state-of-the-art large-scale Datalog systems and verify the efficacy of our techniques and effectiveness of Spark in supporting Datalog-based analytics. PMID:28626296

Using memory-efficient algorithm for large-scale time-domain modeling of surface plasmon polaritons propagation in organic light emitting diodes

NASA Astrophysics Data System (ADS)

Zakirov, Andrey; Belousov, Sergei; Valuev, Ilya; Levchenko, Vadim; Perepelkina, Anastasia; Zempo, Yasunari

2017-10-01

We demonstrate an efficient approach to numerical modeling of optical properties of large-scale structures with typical dimensions much greater than the wavelength of light. For this purpose, we use the finite-difference time-domain (FDTD) method enhanced with a memory efficient Locally Recursive non-Locally Asynchronous (LRnLA) algorithm called DiamondTorre and implemented for General Purpose Graphical Processing Units (GPGPU) architecture. We apply our approach to simulation of optical properties of organic light emitting diodes (OLEDs), which is an essential step in the process of designing OLEDs with improved efficiency. Specifically, we consider a problem of excitation and propagation of surface plasmon polaritons (SPPs) in a typical OLED, which is a challenging task given that SPP decay length can be about two orders of magnitude greater than the wavelength of excitation. We show that with our approach it is possible to extend the simulated volume size sufficiently so that SPP decay dynamics is accounted for. We further consider an OLED with periodically corrugated metallic cathode and show how the SPP decay length can be greatly reduced due to scattering off the corrugation. Ultimately, we compare the performance of our algorithm to the conventional FDTD and demonstrate that our approach can efficiently be used for large-scale FDTD simulations with the use of only a single GPGPU-powered workstation, which is not practically feasible with the conventional FDTD.

Continuous Flow Polymer Synthesis toward Reproducible Large-Scale Production for Efficient Bulk Heterojunction Organic Solar Cells.

PubMed

Pirotte, Geert; Kesters, Jurgen; Verstappen, Pieter; Govaerts, Sanne; Manca, Jean; Lutsen, Laurence; Vanderzande, Dirk; Maes, Wouter

2015-10-12

Organic photovoltaics (OPV) have attracted great interest as a solar cell technology with appealing mechanical, aesthetical, and economies-of-scale features. To drive OPV toward economic viability, low-cost, large-scale module production has to be realized in combination with increased top-quality material availability and minimal batch-to-batch variation. To this extent, continuous flow chemistry can serve as a powerful tool. In this contribution, a flow protocol is optimized for the high performance benzodithiophene-thienopyrroledione copolymer PBDTTPD and the material quality is probed through systematic solar-cell evaluation. A stepwise approach is adopted to turn the batch process into a reproducible and scalable continuous flow procedure. Solar cell devices fabricated using the obtained polymer batches deliver an average power conversion efficiency of 7.2 %. Upon incorporation of an ionic polythiophene-based cathodic interlayer, the photovoltaic performance could be enhanced to a maximum efficiency of 9.1 %. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Combined process automation for large-scale EEG analysis.

PubMed

Sfondouris, John L; Quebedeaux, Tabitha M; Holdgraf, Chris; Musto, Alberto E

2012-01-01

Epileptogenesis is a dynamic process producing increased seizure susceptibility. Electroencephalography (EEG) data provides information critical in understanding the evolution of epileptiform changes throughout epileptic foci. We designed an algorithm to facilitate efficient large-scale EEG analysis via linked automation of multiple data processing steps. Using EEG recordings obtained from electrical stimulation studies, the following steps of EEG analysis were automated: (1) alignment and isolation of pre- and post-stimulation intervals, (2) generation of user-defined band frequency waveforms, (3) spike-sorting, (4) quantification of spike and burst data and (5) power spectral density analysis. This algorithm allows for quicker, more efficient EEG analysis. Copyright © 2011 Elsevier Ltd. All rights reserved.

Joint classification and contour extraction of large 3D point clouds

NASA Astrophysics Data System (ADS)

Hackel, Timo; Wegner, Jan D.; Schindler, Konrad

2017-08-01

We present an effective and efficient method for point-wise semantic classification and extraction of object contours of large-scale 3D point clouds. What makes point cloud interpretation challenging is the sheer size of several millions of points per scan and the non-grid, sparse, and uneven distribution of points. Standard image processing tools like texture filters, for example, cannot handle such data efficiently, which calls for dedicated point cloud labeling methods. It turns out that one of the major drivers for efficient computation and handling of strong variations in point density, is a careful formulation of per-point neighborhoods at multiple scales. This allows, both, to define an expressive feature set and to extract topologically meaningful object contours. Semantic classification and contour extraction are interlaced problems. Point-wise semantic classification enables extracting a meaningful candidate set of contour points while contours help generating a rich feature representation that benefits point-wise classification. These methods are tailored to have fast run time and small memory footprint for processing large-scale, unstructured, and inhomogeneous point clouds, while still achieving high classification accuracy. We evaluate our methods on the semantic3d.net benchmark for terrestrial laser scans with >109 points.

High areal capacity hybrid magnesium-lithium-ion battery with 99.9% Coulombic efficiency for large-scale energy storage.

PubMed

Yoo, Hyun Deog; Liang, Yanliang; Li, Yifei; Yao, Yan

2015-04-01

Hybrid magnesium-lithium-ion batteries (MLIBs) featuring dendrite-free deposition of Mg anode and Li-intercalation cathode are safe alternatives to Li-ion batteries for large-scale energy storage. Here we report for the first time the excellent stability of a high areal capacity MLIB cell and dendrite-free deposition behavior of Mg under high current density (2 mA cm(-2)). The hybrid cell showed no capacity loss for 100 cycles with Coulombic efficiency as high as 99.9%, whereas the control cell with a Li-metal anode only retained 30% of its original capacity with Coulombic efficiency well below 90%. The use of TiS2 as a cathode enabled the highest specific capacity and one of the best rate performances among reported MLIBs. Postmortem analysis of the cycled cells revealed dendrite-free Mg deposition on a Mg anode surface, while mossy Li dendrites were observed covering the Li surface and penetrated into separators in the Li cell. The energy density of a MLIB could be further improved by developing electrolytes with higher salt concentration and wider electrochemical window, leading to new opportunities for its application in large-scale energy storage.

Research of an emergency medical system for mass casualty incidents in Shanghai, China: a system dynamics model

PubMed Central

Liu, Xu; Chen, Haiping; Xue, Chen

2018-01-01

Objectives Emergency medical system for mass casualty incidents (EMS-MCIs) is a global issue. However, China lacks such studies extremely, which cannot meet the requirement of rapid decision-support system. This study aims to realize modeling EMS-MCIs in Shanghai, to improve mass casualty incident (MCI) rescue efficiency in China, and to provide a possible method of making rapid rescue decisions during MCIs. Methods This study established a system dynamics (SD) model of EMS-MCIs using the Vensim DSS program. Intervention scenarios were designed as adjusting scales of MCIs, allocation of ambulances, allocation of emergency medical staff, and efficiency of organization and command. Results Mortality increased with the increasing scale of MCIs, medical rescue capability of hospitals was relatively good, but the efficiency of organization and command was poor, and the prehospital time was too long. Mortality declined significantly when increasing ambulances and improving the efficiency of organization and command; triage and on-site first-aid time were shortened if increasing the availability of emergency medical staff. The effect was the most evident when 2,000 people were involved in MCIs; however, the influence was very small under the scale of 5,000 people. Conclusion The keys to decrease the mortality of MCIs were shortening the prehospital time and improving the efficiency of organization and command. For small-scale MCIs, improving the utilization rate of health resources was important in decreasing the mortality. For large-scale MCIs, increasing the number of ambulances and emergency medical professionals was the core to decrease prehospital time and mortality. For super-large-scale MCIs, increasing health resources was the premise. PMID:29440876

Enhancing Solar Cell Efficiencies through 1-D Nanostructures

PubMed Central

2009-01-01

The current global energy problem can be attributed to insufficient fossil fuel supplies and excessive greenhouse gas emissions resulting from increasing fossil fuel consumption. The huge demand for clean energy potentially can be met by solar-to-electricity conversions. The large-scale use of solar energy is not occurring due to the high cost and inadequate efficiencies of existing solar cells. Nanostructured materials have offered new opportunities to design more efficient solar cells, particularly one-dimensional (1-D) nanomaterials for enhancing solar cell efficiencies. These 1-D nanostructures, including nanotubes, nanowires, and nanorods, offer significant opportunities to improve efficiencies of solar cells by facilitating photon absorption, electron transport, and electron collection; however, tremendous challenges must be conquered before the large-scale commercialization of such cells. This review specifically focuses on the use of 1-D nanostructures for enhancing solar cell efficiencies. Other nanostructured solar cells or solar cells based on bulk materials are not covered in this review. Major topics addressed include dye-sensitized solar cells, quantum-dot-sensitized solar cells, and p-n junction solar cells.

Large-scale fabrication of micro-lens array by novel end-fly-cutting-servo diamond machining.

PubMed

Zhu, Zhiwei; To, Suet; Zhang, Shaojian

2015-08-10

Fast/slow tool servo (FTS/STS) diamond turning is a very promising technique for the generation of micro-lens array (MLA). However, it is still a challenge to process MLA in large scale due to certain inherent limitations of this technique. In the present study, a novel ultra-precision diamond cutting method, as the end-fly-cutting-servo (EFCS) system, is adopted and investigated for large-scale generation of MLA. After a detailed discussion of the characteristic advantages for processing MLA, the optimal toolpath generation strategy for the EFCS is developed with consideration of the geometry and installation pose of the diamond tool. A typical aspheric MLA over a large area is experimentally fabricated, and the resulting form accuracy, surface micro-topography and machining efficiency are critically investigated. The result indicates that the MLA with homogeneous quality over the whole area is obtained. Besides, high machining efficiency, extremely small volume of control points for the toolpath, and optimal usage of system dynamics of the machine tool during the whole cutting can be simultaneously achieved.

k-neighborhood Decentralization: A Comprehensive Solution to Index the UMLS for Large Scale Knowledge Discovery

PubMed Central

Xiang, Yang; Lu, Kewei; James, Stephen L.; Borlawsky, Tara B.; Huang, Kun; Payne, Philip R.O.

2011-01-01

The Unified Medical Language System (UMLS) is the largest thesaurus in the biomedical informatics domain. Previous works have shown that knowledge constructs comprised of transitively-associated UMLS concepts are effective for discovering potentially novel biomedical hypotheses. However, the extremely large size of the UMLS becomes a major challenge for these applications. To address this problem, we designed a k-neighborhood Decentralization Labeling Scheme (kDLS) for the UMLS, and the corresponding method to effectively evaluate the kDLS indexing results. kDLS provides a comprehensive solution for indexing the UMLS for very efficient large scale knowledge discovery. We demonstrated that it is highly effective to use kDLS paths to prioritize disease-gene relations across the whole genome, with extremely high fold-enrichment values. To our knowledge, this is the first indexing scheme capable of supporting efficient large scale knowledge discovery on the UMLS as a whole. Our expectation is that kDLS will become a vital engine for retrieving information and generating hypotheses from the UMLS for future medical informatics applications. PMID:22154838

k-Neighborhood decentralization: a comprehensive solution to index the UMLS for large scale knowledge discovery.

PubMed

Xiang, Yang; Lu, Kewei; James, Stephen L; Borlawsky, Tara B; Huang, Kun; Payne, Philip R O

2012-04-01

The Unified Medical Language System (UMLS) is the largest thesaurus in the biomedical informatics domain. Previous works have shown that knowledge constructs comprised of transitively-associated UMLS concepts are effective for discovering potentially novel biomedical hypotheses. However, the extremely large size of the UMLS becomes a major challenge for these applications. To address this problem, we designed a k-neighborhood Decentralization Labeling Scheme (kDLS) for the UMLS, and the corresponding method to effectively evaluate the kDLS indexing results. kDLS provides a comprehensive solution for indexing the UMLS for very efficient large scale knowledge discovery. We demonstrated that it is highly effective to use kDLS paths to prioritize disease-gene relations across the whole genome, with extremely high fold-enrichment values. To our knowledge, this is the first indexing scheme capable of supporting efficient large scale knowledge discovery on the UMLS as a whole. Our expectation is that kDLS will become a vital engine for retrieving information and generating hypotheses from the UMLS for future medical informatics applications. Copyright © 2011 Elsevier Inc. All rights reserved.

A novel artificial fish swarm algorithm for solving large-scale reliability-redundancy application problem.

PubMed

He, Qiang; Hu, Xiangtao; Ren, Hong; Zhang, Hongqi

2015-11-01

A novel artificial fish swarm algorithm (NAFSA) is proposed for solving large-scale reliability-redundancy allocation problem (RAP). In NAFSA, the social behaviors of fish swarm are classified in three ways: foraging behavior, reproductive behavior, and random behavior. The foraging behavior designs two position-updating strategies. And, the selection and crossover operators are applied to define the reproductive ability of an artificial fish. For the random behavior, which is essentially a mutation strategy, the basic cloud generator is used as the mutation operator. Finally, numerical results of four benchmark problems and a large-scale RAP are reported and compared. NAFSA shows good performance in terms of computational accuracy and computational efficiency for large scale RAP. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

On Efficient Multigrid Methods for Materials Processing Flows with Small Particles

NASA Technical Reports Server (NTRS)

Thomas, James (Technical Monitor); Diskin, Boris; Harik, VasylMichael

2004-01-01

Multiscale modeling of materials requires simulations of multiple levels of structural hierarchy. The computational efficiency of numerical methods becomes a critical factor for simulating large physical systems with highly desperate length scales. Multigrid methods are known for their superior efficiency in representing/resolving different levels of physical details. The efficiency is achieved by employing interactively different discretizations on different scales (grids). To assist optimization of manufacturing conditions for materials processing with numerous particles (e.g., dispersion of particles, controlling flow viscosity and clusters), a new multigrid algorithm has been developed for a case of multiscale modeling of flows with small particles that have various length scales. The optimal efficiency of the algorithm is crucial for accurate predictions of the effect of processing conditions (e.g., pressure and velocity gradients) on the local flow fields that control the formation of various microstructures or clusters.

Large-Scale Advanced Prop-Fan (LAP)

NASA Technical Reports Server (NTRS)

Degeorge, C. L.

1988-01-01

In recent years, considerable attention has been directed toward improving aircraft fuel efficiency. Analytical studies and research with wind tunnel models have demonstrated that the high inherent efficiency of low speed turboprop propulsion systems may now be extended to the Mach .8 flight regime of today's commercial airliners. This can be accomplished with a propeller, employing a large number of thin highly swept blades. The term Prop-Fan has been coined to describe such a propulsion system. In 1983 the NASA-Lewis Research Center contracted with Hamilton Standard to design, build and test a near full scale Prop-Fan, designated the Large Scale Advanced Prop-Fan (LAP). This report provides a detailed description of the LAP program. The assumptions and analytical procedures used in the design of Prop-Fan system components are discussed in detail. The manufacturing techniques used in the fabrication of the Prop-Fan are presented. Each of the tests run during the course of the program are also discussed and the major conclusions derived from them stated.

Evaluation of biochar powder on oxygen supply efficiency and global warming potential during mainstream large-scale aerobic composting.

PubMed

He, Xueqin; Chen, Longjian; Han, Lujia; Liu, Ning; Cui, Ruxiu; Yin, Hongjie; Huang, Guangqun

2017-12-01

This study investigated the effects of biochar powder on oxygen supply efficiency and global warming potential (GWP) in the large-scale aerobic composting pattern which includes cyclical forced-turning with aeration at the bottom of composting tanks in China. A 55-day large-scale aerobic composting experiment was conducted in two different groups without and with 10% biochar powder addition (by weight). The results show that biochar powder improves the holding ability of oxygen, and the duration time (O 2 >5%) is around 80%. The composting process with above pattern significantly reduce CH 4 and N 2 O emissions compared to the static or turning-only styles. Considering the average GWP of the BC group was 19.82% lower than that of the CK group, it suggests that rational addition of biochar powder has the potential to reduce the energy consumption of turning, improve effectiveness of the oxygen supply, and reduce comprehensive greenhouse effects. Copyright © 2017. Published by Elsevier Ltd.

Leaky Integrate and Fire Neuron by Charge-Discharge Dynamics in Floating-Body MOSFET.

PubMed

Dutta, Sangya; Kumar, Vinay; Shukla, Aditya; Mohapatra, Nihar R; Ganguly, Udayan

2017-08-15

Neuro-biology inspired Spiking Neural Network (SNN) enables efficient learning and recognition tasks. To achieve a large scale network akin to biology, a power and area efficient electronic neuron is essential. Earlier, we had demonstrated an LIF neuron by a novel 4-terminal impact ionization based n+/p/n+ with an extended gate (gated-INPN) device by physics simulation. Excellent improvement in area and power compared to conventional analog circuit implementations was observed. In this paper, we propose and experimentally demonstrate a compact conventional 3-terminal partially depleted (PD) SOI- MOSFET (100 nm gate length) to replace the 4-terminal gated-INPN device. Impact ionization (II) induced floating body effect in SOI-MOSFET is used to capture LIF neuron behavior to demonstrate spiking frequency dependence on input. MHz operation enables attractive hardware acceleration compared to biology. Overall, conventional PD-SOI-CMOS technology enables very-large-scale-integration (VLSI) which is essential for biology scale (~10 11 neuron based) large neural networks.

Large-scale inverse model analyses employing fast randomized data reduction

NASA Astrophysics Data System (ADS)

Lin, Youzuo; Le, Ellen B.; O'Malley, Daniel; Vesselinov, Velimir V.; Bui-Thanh, Tan

2017-08-01

When the number of observations is large, it is computationally challenging to apply classical inverse modeling techniques. We have developed a new computationally efficient technique for solving inverse problems with a large number of observations (e.g., on the order of 107 or greater). Our method, which we call the randomized geostatistical approach (RGA), is built upon the principal component geostatistical approach (PCGA). We employ a data reduction technique combined with the PCGA to improve the computational efficiency and reduce the memory usage. Specifically, we employ a randomized numerical linear algebra technique based on a so-called "sketching" matrix to effectively reduce the dimension of the observations without losing the information content needed for the inverse analysis. In this way, the computational and memory costs for RGA scale with the information content rather than the size of the calibration data. Our algorithm is coded in Julia and implemented in the MADS open-source high-performance computational framework (http://mads.lanl.gov). We apply our new inverse modeling method to invert for a synthetic transmissivity field. Compared to a standard geostatistical approach (GA), our method is more efficient when the number of observations is large. Most importantly, our method is capable of solving larger inverse problems than the standard GA and PCGA approaches. Therefore, our new model inversion method is a powerful tool for solving large-scale inverse problems. The method can be applied in any field and is not limited to hydrogeological applications such as the characterization of aquifer heterogeneity.

Large-scale bioenergy production: how to resolve sustainability trade-offs?

NASA Astrophysics Data System (ADS)

Humpenöder, Florian; Popp, Alexander; Bodirsky, Benjamin Leon; Weindl, Isabelle; Biewald, Anne; Lotze-Campen, Hermann; Dietrich, Jan Philipp; Klein, David; Kreidenweis, Ulrich; Müller, Christoph; Rolinski, Susanne; Stevanovic, Miodrag

2018-02-01

Large-scale 2nd generation bioenergy deployment is a key element of 1.5 °C and 2 °C transformation pathways. However, large-scale bioenergy production might have negative sustainability implications and thus may conflict with the Sustainable Development Goal (SDG) agenda. Here, we carry out a multi-criteria sustainability assessment of large-scale bioenergy crop production throughout the 21st century (300 EJ in 2100) using a global land-use model. Our analysis indicates that large-scale bioenergy production without complementary measures results in negative effects on the following sustainability indicators: deforestation, CO2 emissions from land-use change, nitrogen losses, unsustainable water withdrawals and food prices. One of our main findings is that single-sector environmental protection measures next to large-scale bioenergy production are prone to involve trade-offs among these sustainability indicators—at least in the absence of more efficient land or water resource use. For instance, if bioenergy production is accompanied by forest protection, deforestation and associated emissions (SDGs 13 and 15) decline substantially whereas food prices (SDG 2) increase. However, our study also shows that this trade-off strongly depends on the development of future food demand. In contrast to environmental protection measures, we find that agricultural intensification lowers some side-effects of bioenergy production substantially (SDGs 13 and 15) without generating new trade-offs—at least among the sustainability indicators considered here. Moreover, our results indicate that a combination of forest and water protection schemes, improved fertilization efficiency, and agricultural intensification would reduce the side-effects of bioenergy production most comprehensively. However, although our study includes more sustainability indicators than previous studies on bioenergy side-effects, our study represents only a small subset of all indicators relevant for the SDG agenda. Based on this, we argue that the development of policies for regulating externalities of large-scale bioenergy production should rely on broad sustainability assessments to discover potential trade-offs with the SDG agenda before implementation.

Parallel Large-scale Semidefinite Programming for Strong Electron Correlation: Using Correlation and Entanglement in the Design of Efficient Energy-Transfer Mechanisms

DTIC Science & Technology

2014-09-24

which nature uses strong electron correlation for efficient energy transfer, particularly in photosynthesis and bioluminescence, (ii) providing an...strong electron correlation for efficient energy transfer, particularly in photosynthesis and bioluminescence, (ii) providing an innovative paradigm...efficient energy transfer, particularly in photosynthesis and bioluminescence, (ii) providing an innovative paradigm for energy transfer in photovoltaic

High Quantum Efficiency OLED Lighting Systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Shiang, Joseph

The overall goal of the program was to apply improvements in light outcoupling technology to a practical large area plastic luminaire, and thus enable the product vision of an extremely thin form factor high efficiency large area light source. The target substrate was plastic and the baseline device was operating at 35 LPW at the start of the program. The target LPW of the program was a >2x improvement in the LPW efficacy and the overall amount of light to be delivered was relatively high 900 lumens. Despite the extremely difficult challenges associated with scaling up a wet solution processmore » on plastic substrates, the program was able to make substantial progress. A small molecule wet solution process was successfully implemented on plastic substrates with almost no loss in efficiency in transitioning from the laboratory scale glass to large area plastic substrates. By transitioning to a small molecule based process, the LPW entitlement increased from 35 LPW to 60 LPW. A further 10% improvement in outcoupling efficiency was demonstrated via the use of a highly reflecting cathode, which reduced absorptive loss in the OLED device. The calculated potential improvement in some cases is even larger, ~30%, and thus there is considerable room for optimism in improving the net light coupling efficacy, provided absorptive loss mechanisms are eliminated. Further improvements are possible if scattering schemes such as the silver nanowire based hard coat structure are fully developed. The wet coating processes were successfully scaled to large area plastic substrate and resulted in the construction of a 900 lumens luminaire device.« less

Phytoplankton plasticity drives large variability in carbon fixation efficiency

NASA Astrophysics Data System (ADS)

Ayata, Sakina-Dorothée.; Lévy, Marina; Aumont, Olivier; Resplandy, Laure; Tagliabue, Alessandro; Sciandra, Antoine; Bernard, Olivier

2014-12-01

Phytoplankton C:N stoichiometry is highly flexible due to physiological plasticity, which could lead to high variations in carbon fixation efficiency (carbon consumption relative to nitrogen). However, the magnitude, as well as the spatial and temporal scales of variability, remains poorly constrained. We used a high-resolution biogeochemical model resolving various scales from small to high, spatially and temporally, in order to quantify and better understand this variability. We find that phytoplankton C:N ratio is highly variable at all spatial and temporal scales (5-12 molC/molN), from mesoscale to regional scale, and is mainly driven by nitrogen supply. Carbon fixation efficiency varies accordingly at all scales (±30%), with higher values under oligotrophic conditions and lower values under eutrophic conditions. Hence, phytoplankton plasticity may act as a buffer by attenuating carbon sequestration variability. Our results have implications for in situ estimations of C:N ratios and for future predictions under high CO2 world.

Large-scale motions in the universe: Using clusters of galaxies as tracers

NASA Technical Reports Server (NTRS)

Gramann, Mirt; Bahcall, Neta A.; Cen, Renyue; Gott, J. Richard

1995-01-01

Can clusters of galaxies be used to trace the large-scale peculiar velocity field of the universe? We answer this question by using large-scale cosmological simulations to compare the motions of rich clusters of galaxies with the motion of the underlying matter distribution. Three models are investigated: Omega = 1 and Omega = 0.3 cold dark matter (CDM), and Omega = 0.3 primeval baryonic isocurvature (PBI) models, all normalized to the Cosmic Background Explorer (COBE) background fluctuations. We compare the cluster and mass distribution of peculiar velocities, bulk motions, velocity dispersions, and Mach numbers as a function of scale for R greater than or = 50/h Mpc. We also present the large-scale velocity and potential maps of clusters and of the matter. We find that clusters of galaxies trace well the large-scale velocity field and can serve as an efficient tool to constrain cosmological models. The recently reported bulk motion of clusters 689 +/- 178 km/s on approximately 150/h Mpc scale (Lauer & Postman 1994) is larger than expected in any of the models studied (less than or = 190 +/- 78 km/s).

How does the connectivity of open-framework conglomerates within multi-scale hierarchical fluvial architecture affect oil-sweep efficiency in waterflooding?

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gershenzon, Naum I.; Soltanian, Mohamad Reza; Ritzi, Robert W.

Understanding multi-phase fluid flow and transport processes within aquifers, candidate reservoirs for CO 2 sequestration, and petroleum reservoirs requires understanding a diverse set of geologic properties of the aquifer or reservoir, over a wide range of spatial and temporal scales. We focus on multiphase flow dynamics with wetting (e.g., water) and non-wetting (e.g., gas or oil) fluids, with one invading another. This problem is of general interest in a number of fields and is illustrated here by considering the sweep efficiency of oil during a waterflood. Using a relatively fine-resolution grid throughout a relatively large domain in these simulations andmore » probing the results with advanced scientific visualization tools (Reservoir Visualization Analysis [RVA]/ ParaView software) promote a better understanding of how smaller-scale features affect the aggregate behavior at larger scales. We studied the effects on oil-sweep efficiency of the proportion, hierarchical organization, and connectivity of high-permeability open-framework conglomerate (OFC) cross-sets within the multi-scale stratal architecture found in fluvial deposits. We further analyzed oil production rate, water breakthrough time, and spatial and temporal distribution of residual oil saturation. As expected, the effective permeability of the reservoir exhibits large-scale anisotropy created by the organization of OFC cross-sets within unit bars, and the organization of unit bars within compound- bars. As a result, oil-sweep efficiency critically depends on the direction of the pressure gradient. However, contrary to expectations, the total amount of trapped oil due to the effect of capillary trapping does not depend on the magnitude of the pressure gradient within the examined range. Hence the pressure difference between production and injection wells does not affect sweep efficiency; although the spatial distribution of oil remaining in the reservoir depends on this value. Whether or not clusters of connected OFC span the domain affects only the absolute rate of oil production—not sweep efficiency.« less

How does the connectivity of open-framework conglomerates within multi-scale hierarchical fluvial architecture affect oil-sweep efficiency in waterflooding?

DOE PAGES

Gershenzon, Naum I.; Soltanian, Mohamad Reza; Ritzi, Robert W.; ...

2015-10-23

Understanding multi-phase fluid flow and transport processes within aquifers, candidate reservoirs for CO 2 sequestration, and petroleum reservoirs requires understanding a diverse set of geologic properties of the aquifer or reservoir, over a wide range of spatial and temporal scales. We focus on multiphase flow dynamics with wetting (e.g., water) and non-wetting (e.g., gas or oil) fluids, with one invading another. This problem is of general interest in a number of fields and is illustrated here by considering the sweep efficiency of oil during a waterflood. Using a relatively fine-resolution grid throughout a relatively large domain in these simulations andmore » probing the results with advanced scientific visualization tools (Reservoir Visualization Analysis [RVA]/ ParaView software) promote a better understanding of how smaller-scale features affect the aggregate behavior at larger scales. We studied the effects on oil-sweep efficiency of the proportion, hierarchical organization, and connectivity of high-permeability open-framework conglomerate (OFC) cross-sets within the multi-scale stratal architecture found in fluvial deposits. We further analyzed oil production rate, water breakthrough time, and spatial and temporal distribution of residual oil saturation. As expected, the effective permeability of the reservoir exhibits large-scale anisotropy created by the organization of OFC cross-sets within unit bars, and the organization of unit bars within compound- bars. As a result, oil-sweep efficiency critically depends on the direction of the pressure gradient. However, contrary to expectations, the total amount of trapped oil due to the effect of capillary trapping does not depend on the magnitude of the pressure gradient within the examined range. Hence the pressure difference between production and injection wells does not affect sweep efficiency; although the spatial distribution of oil remaining in the reservoir depends on this value. Whether or not clusters of connected OFC span the domain affects only the absolute rate of oil production—not sweep efficiency.« less

A link between nonlinear self-organization and dissipation in drift-wave turbulence

DOE Office of Scientific and Technical Information (OSTI.GOV)

Manz, P.; Birkenmeier, G.; Stroth, U.

Structure formation and self-organization in two-dimensional drift-wave turbulence show up in many different faces. Fluctuation data from a magnetized plasma are analyzed and three mechanisms transferring kinetic energy to large-scale structures are identified. Beside the common vortex merger, clustering of vortices constituting a large-scale strain field and vortex thinning, where due to the interactions of vortices of different scales larger vortices are amplified by the smaller ones, are observed. The vortex thinning mechanism appears to be the most efficient one to generate large scale structures in drift-wave turbulence. Vortex merging as well as vortex clustering are accompanied by strong energymore » transfer to small-scale noncoherent fluctuations (dissipation) balancing the negative entropy generation due to the self-organization process.« less

Development of a gene synthesis platform for the efficient large scale production of small genes encoding animal toxins.

PubMed

Sequeira, Ana Filipa; Brás, Joana L A; Guerreiro, Catarina I P D; Vincentelli, Renaud; Fontes, Carlos M G A

2016-12-01

Gene synthesis is becoming an important tool in many fields of recombinant DNA technology, including recombinant protein production. De novo gene synthesis is quickly replacing the classical cloning and mutagenesis procedures and allows generating nucleic acids for which no template is available. In addition, when coupled with efficient gene design algorithms that optimize codon usage, it leads to high levels of recombinant protein expression. Here, we describe the development of an optimized gene synthesis platform that was applied to the large scale production of small genes encoding venom peptides. This improved gene synthesis method uses a PCR-based protocol to assemble synthetic DNA from pools of overlapping oligonucleotides and was developed to synthesise multiples genes simultaneously. This technology incorporates an accurate, automated and cost effective ligation independent cloning step to directly integrate the synthetic genes into an effective Escherichia coli expression vector. The robustness of this technology to generate large libraries of dozens to thousands of synthetic nucleic acids was demonstrated through the parallel and simultaneous synthesis of 96 genes encoding animal toxins. An automated platform was developed for the large-scale synthesis of small genes encoding eukaryotic toxins. Large scale recombinant expression of synthetic genes encoding eukaryotic toxins will allow exploring the extraordinary potency and pharmacological diversity of animal venoms, an increasingly valuable but unexplored source of lead molecules for drug discovery.

A Metascalable Computing Framework for Large Spatiotemporal-Scale Atomistic Simulations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nomura, K; Seymour, R; Wang, W

2009-02-17

A metascalable (or 'design once, scale on new architectures') parallel computing framework has been developed for large spatiotemporal-scale atomistic simulations of materials based on spatiotemporal data locality principles, which is expected to scale on emerging multipetaflops architectures. The framework consists of: (1) an embedded divide-and-conquer (EDC) algorithmic framework based on spatial locality to design linear-scaling algorithms for high complexity problems; (2) a space-time-ensemble parallel (STEP) approach based on temporal locality to predict long-time dynamics, while introducing multiple parallelization axes; and (3) a tunable hierarchical cellular decomposition (HCD) parallelization framework to map these O(N) algorithms onto a multicore cluster based onmore » hybrid implementation combining message passing and critical section-free multithreading. The EDC-STEP-HCD framework exposes maximal concurrency and data locality, thereby achieving: (1) inter-node parallel efficiency well over 0.95 for 218 billion-atom molecular-dynamics and 1.68 trillion electronic-degrees-of-freedom quantum-mechanical simulations on 212,992 IBM BlueGene/L processors (superscalability); (2) high intra-node, multithreading parallel efficiency (nanoscalability); and (3) nearly perfect time/ensemble parallel efficiency (eon-scalability). The spatiotemporal scale covered by MD simulation on a sustained petaflops computer per day (i.e. petaflops {center_dot} day of computing) is estimated as NT = 2.14 (e.g. N = 2.14 million atoms for T = 1 microseconds).« less

An economical device for carbon supplement in large-scale micro-algae production.

PubMed

Su, Zhenfeng; Kang, Ruijuan; Shi, Shaoyuan; Cong, Wei; Cai, Zhaoling

2008-10-01

One simple but efficient carbon-supplying device was designed and developed, and the correlative carbon-supplying technology was described. The absorbing characterization of this device was studied. The carbon-supplying system proved to be economical for large-scale cultivation of Spirulina sp. in an outdoor raceway pond, and the gaseous carbon dioxide absorptivity was enhanced above 78%, which could reduce the production cost greatly.

SPECTRAL LINE DE-CONFUSION IN AN INTENSITY MAPPING SURVEY

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cheng, Yun-Ting; Bock, James; Bradford, C. Matt

2016-12-01

Spectral line intensity mapping (LIM) has been proposed as a promising tool to efficiently probe the cosmic reionization and the large-scale structure. Without detecting individual sources, LIM makes use of all available photons and measures the integrated light in the source confusion limit to efficiently map the three-dimensional matter distribution on large scales as traced by a given emission line. One particular challenge is the separation of desired signals from astrophysical continuum foregrounds and line interlopers. Here we present a technique to extract large-scale structure information traced by emission lines from different redshifts, embedded in a three-dimensional intensity mapping data cube.more » The line redshifts are distinguished by the anisotropic shape of the power spectra when projected onto a common coordinate frame. We consider the case where high-redshift [C ii] lines are confused with multiple low-redshift CO rotational lines. We present a semi-analytic model for [C ii] and CO line estimates based on the cosmic infrared background measurements, and show that with a modest instrumental noise level and survey geometry, the large-scale [C ii] and CO power spectrum amplitudes can be successfully extracted from a confusion-limited data set, without external information. We discuss the implications and limits of this technique for possible LIM experiments.« less

Scaling up to address data science challenges

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wendelberger, Joanne R.

Statistics and Data Science provide a variety of perspectives and technical approaches for exploring and understanding Big Data. Partnerships between scientists from different fields such as statistics, machine learning, computer science, and applied mathematics can lead to innovative approaches for addressing problems involving increasingly large amounts of data in a rigorous and effective manner that takes advantage of advances in computing. Here, this article will explore various challenges in Data Science and will highlight statistical approaches that can facilitate analysis of large-scale data including sampling and data reduction methods, techniques for effective analysis and visualization of large-scale simulations, and algorithmsmore » and procedures for efficient processing.« less

Scaling up to address data science challenges

DOE PAGES

Wendelberger, Joanne R.

2017-04-27

Statistics and Data Science provide a variety of perspectives and technical approaches for exploring and understanding Big Data. Partnerships between scientists from different fields such as statistics, machine learning, computer science, and applied mathematics can lead to innovative approaches for addressing problems involving increasingly large amounts of data in a rigorous and effective manner that takes advantage of advances in computing. Here, this article will explore various challenges in Data Science and will highlight statistical approaches that can facilitate analysis of large-scale data including sampling and data reduction methods, techniques for effective analysis and visualization of large-scale simulations, and algorithmsmore » and procedures for efficient processing.« less

Cram

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gamblin, T.

2014-08-29

Large-scale systems like Sequoia allow running small numbers of very large (1M+ process) jobs, but their resource managers and schedulers do not allow large numbers of small (4, 8, 16, etc.) process jobs to run efficiently. Cram is a tool that allows users to launch many small MPI jobs within one large partition, and to overcome the limitations of current resource management software for large ensembles of jobs.

One-Pot Large-Scale Synthesis of Carbon Quantum Dots: Efficient Cathode Interlayers for Polymer Solar Cells.

PubMed

Yang, Yuzhao; Lin, Xiaofeng; Li, Wenlang; Ou, Jiemei; Yuan, Zhongke; Xie, Fangyan; Hong, Wei; Yu, Dingshan; Ma, Yuguang; Chi, Zhenguo; Chen, Xudong

2017-05-03

Cathode interlayers (CILs) with low-cost, low-toxicity, and excellent cathode modification ability are necessary for the large-scale industrialization of polymer solar cells (PSCs). In this contribution, we demonstrated one-pot synthesized carbon quantum dots (C-dots) with high production to serve as efficient CIL for inverted PSCs. The C-dots were synthesized by a facile, economical microwave pyrolysis in a household microwave oven within 7 min. Ultraviolet photoelectron spectroscopy (UPS) studies showed that the C-dots possessed the ability to form a dipole at the interface, resulting in the decrease of the work function (WF) of cathode. External quantum efficiency (EQE) measurements and 2D excitation-emission topographical maps revealed that the C-dots down-shifted the high energy near-ultraviolet light to low energy visible light to generate more photocurrent. Remarkably improvement of power conversion efficiency (PCE) was attained by incorporation of C-dots as CIL. The PCE was boosted up from 4.14% to 8.13% with C-dots as CIL, which is one of the best efficiency for i-PSCs used carbon based materials as interlayers. These results demonstrated that C-dots can be a potential candidate for future low cost and large area PSCs producing.

Efficient estimation and large-scale evaluation of lateral chromatic aberration for digital image forensics

NASA Astrophysics Data System (ADS)

Gloe, Thomas; Borowka, Karsten; Winkler, Antje

2010-01-01

The analysis of lateral chromatic aberration forms another ingredient for a well equipped toolbox of an image forensic investigator. Previous work proposed its application to forgery detection1 and image source identification.2 This paper takes a closer look on the current state-of-the-art method to analyse lateral chromatic aberration and presents a new approach to estimate lateral chromatic aberration in a runtime-efficient way. Employing a set of 11 different camera models including 43 devices, the characteristic of lateral chromatic aberration is investigated in a large-scale. The reported results point to general difficulties that have to be considered in real world investigations.

High-Performance Computing Unlocks Innovation at NREL - Video Text Version

Science.gov Websites

scales, data visualizations and large-scale modeling provide insights and test new ideas. But this type most energy-efficient data center in the world. NREL and Hewlett-Packard won an R&D 100 award-the

Giant nonlinear response at a plasmonic nanofocus drives efficient four-wave mixing

NASA Astrophysics Data System (ADS)

Nielsen, Michael P.; Shi, Xingyuan; Dichtl, Paul; Maier, Stefan A.; Oulton, Rupert F.

2017-12-01

Efficient optical frequency mixing typically must accumulate over large interaction lengths because nonlinear responses in natural materials are inherently weak. This limits the efficiency of mixing processes owing to the requirement of phase matching. Here, we report efficient four-wave mixing (FWM) over micrometer-scale interaction lengths at telecommunications wavelengths on silicon. We used an integrated plasmonic gap waveguide that strongly confines light within a nonlinear organic polymer. The gap waveguide intensifies light by nanofocusing it to a mode cross-section of a few tens of nanometers, thus generating a nonlinear response so strong that efficient FWM accumulates over wavelength-scale distances. This technique opens up nonlinear optics to a regime of relaxed phase matching, with the possibility of compact, broadband, and efficient frequency mixing integrated with silicon photonics.

Managing Vocabulary Mapping Services

PubMed Central

Che, Chengjian; Monson, Kent; Poon, Kasey B.; Shakib, Shaun C.; Lau, Lee Min

2005-01-01

The efficient management and maintenance of large-scale and high-quality vocabulary mapping is an operational challenge. The 3M Health Information Systems (HIS) Healthcare Data Dictionary (HDD) group developed an information management system to provide controlled mapping services, resulting in improved efficiency and quality maintenance. PMID:16779203

Tuning Chemical Potential Difference across Alternately Doped Graphene p-n Junctions for High-Efficiency Photodetection.

PubMed

Lin, Li; Xu, Xiang; Yin, Jianbo; Sun, Jingyu; Tan, Zhenjun; Koh, Ai Leen; Wang, Huan; Peng, Hailin; Chen, Yulin; Liu, Zhongfan

2016-07-13

Being atomically thin, graphene-based p-n junctions hold great promise for applications in ultrasmall high-efficiency photodetectors. It is well-known that the efficiency of such photodetectors can be improved by optimizing the chemical potential difference of the graphene p-n junction. However, to date, such tuning has been limited to a few hundred millielectronvolts. To improve this critical parameter, here we report that using a temperature-controlled chemical vapor deposition process, we successfully achieved modulation-doped growth of an alternately nitrogen- and boron-doped graphene p-n junction with a tunable chemical potential difference up to 1 eV. Furthermore, such p-n junction structure can be prepared on a large scale with stable, uniform, and substitutional doping and exhibits a single-crystalline nature. This work provides a feasible method for synthesizing low-cost, large-scale, high efficiency graphene p-n junctions, thus facilitating their applications in optoelectronic and energy conversion devices.

A robust and scalable neuromorphic communication system by combining synaptic time multiplexing and MIMO-OFDM.

PubMed

Srinivasa, Narayan; Zhang, Deying; Grigorian, Beayna

2014-03-01

This paper describes a novel architecture for enabling robust and efficient neuromorphic communication. The architecture combines two concepts: 1) synaptic time multiplexing (STM) that trades space for speed of processing to create an intragroup communication approach that is firing rate independent and offers more flexibility in connectivity than cross-bar architectures and 2) a wired multiple input multiple output (MIMO) communication with orthogonal frequency division multiplexing (OFDM) techniques to enable a robust and efficient intergroup communication for neuromorphic systems. The MIMO-OFDM concept for the proposed architecture was analyzed by simulating large-scale spiking neural network architecture. Analysis shows that the neuromorphic system with MIMO-OFDM exhibits robust and efficient communication while operating in real time with a high bit rate. Through combining STM with MIMO-OFDM techniques, the resulting system offers a flexible and scalable connectivity as well as a power and area efficient solution for the implementation of very large-scale spiking neural architectures in hardware.

Process configuration of Liquid-nitrogen Energy Storage System (LESS) for maximum turnaround efficiency

NASA Astrophysics Data System (ADS)

Dutta, Rohan; Ghosh, Parthasarathi; Chowdhury, Kanchan

2017-12-01

Diverse power generation sector requires energy storage due to penetration of variable renewable energy sources and use of CO2 capture plants with fossil fuel based power plants. Cryogenic energy storage being large-scale, decoupled system with capability of producing large power in the range of MWs is one of the options. The drawback of these systems is low turnaround efficiencies due to liquefaction processes being highly energy intensive. In this paper, the scopes of improving the turnaround efficiency of such a plant based on liquid Nitrogen were identified and some of them were addressed. A method using multiple stages of reheat and expansion was proposed for improved turnaround efficiency from 22% to 47% using four such stages in the cycle. The novelty here is the application of reheating in a cryogenic system and utilization of waste heat for that purpose. Based on the study, process conditions for a laboratory-scale setup were determined and presented here.

FAST MAGNETIC FIELD AMPLIFICATION IN THE EARLY UNIVERSE: GROWTH OF COLLISIONLESS PLASMA INSTABILITIES IN TURBULENT MEDIA

DOE Office of Scientific and Technical Information (OSTI.GOV)

Falceta-Gonçalves, D.; Kowal, G.

2015-07-20

In this work we report on a numerical study of the cosmic magnetic field amplification due to collisionless plasma instabilities. The collisionless magnetohydrodynamic equations derived account for the pressure anisotropy that leads, in specific conditions, to the firehose and mirror instabilities. We study the time evolution of seed fields in turbulence under the influence of such instabilities. An approximate analytical time evolution of the magnetic field is provided. The numerical simulations and the analytical predictions are compared. We found that (i) amplification of the magnetic field was efficient in firehose-unstable turbulent regimes, but not in the mirror-unstable models; (ii) the growthmore » rate of the magnetic energy density is much faster than the turbulent dynamo; and (iii) the efficient amplification occurs at small scales. The analytical prediction for the correlation between the growth timescales and pressure anisotropy is confirmed by the numerical simulations. These results reinforce the idea that pressure anisotropies—driven naturally in a turbulent collisionless medium, e.g., the intergalactic medium, could efficiently amplify the magnetic field in the early universe (post-recombination era), previous to the collapse of the first large-scale gravitational structures. This mechanism, though fast for the small-scale fields (∼kpc scales), is unable to provide relatively strong magnetic fields at large scales. Other mechanisms that were not accounted for here (e.g., collisional turbulence once instabilities are quenched, velocity shear, or gravitationally induced inflows of gas into galaxies and clusters) could operate afterward to build up large-scale coherent field structures in the long time evolution.« less

Interface COMSOL-PHREEQC (iCP), an efficient numerical framework for the solution of coupled multiphysics and geochemistry

NASA Astrophysics Data System (ADS)

Nardi, Albert; Idiart, Andrés; Trinchero, Paolo; de Vries, Luis Manuel; Molinero, Jorge

2014-08-01

This paper presents the development, verification and application of an efficient interface, denoted as iCP, which couples two standalone simulation programs: the general purpose Finite Element framework COMSOL Multiphysics® and the geochemical simulator PHREEQC. The main goal of the interface is to maximize the synergies between the aforementioned codes, providing a numerical platform that can efficiently simulate a wide number of multiphysics problems coupled with geochemistry. iCP is written in Java and uses the IPhreeqc C++ dynamic library and the COMSOL Java-API. Given the large computational requirements of the aforementioned coupled models, special emphasis has been placed on numerical robustness and efficiency. To this end, the geochemical reactions are solved in parallel by balancing the computational load over multiple threads. First, a benchmark exercise is used to test the reliability of iCP regarding flow and reactive transport. Then, a large scale thermo-hydro-chemical (THC) problem is solved to show the code capabilities. The results of the verification exercise are successfully compared with those obtained using PHREEQC and the application case demonstrates the scalability of a large scale model, at least up to 32 threads.

Blazing Signature Filter: a library for fast pairwise similarity comparisons

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lee, Joon-Yong; Fujimoto, Grant M.; Wilson, Ryan

Identifying similarities between datasets is a fundamental task in data mining and has become an integral part of modern scientific investigation. Whether the task is to identify co-expressed genes in large-scale expression surveys or to predict combinations of gene knockouts which would elicit a similar phenotype, the underlying computational task is often a multi-dimensional similarity test. As datasets continue to grow, improvements to the efficiency, sensitivity or specificity of such computation will have broad impacts as it allows scientists to more completely explore the wealth of scientific data. A significant practical drawback of large-scale data mining is the vast majoritymore » of pairwise comparisons are unlikely to be relevant, meaning that they do not share a signature of interest. It is therefore essential to efficiently identify these unproductive comparisons as rapidly as possible and exclude them from more time-intensive similarity calculations. The Blazing Signature Filter (BSF) is a highly efficient pairwise similarity algorithm which enables extensive data mining within a reasonable amount of time. The algorithm transforms datasets into binary metrics, allowing it to utilize the computationally efficient bit operators and provide a coarse measure of similarity. As a result, the BSF can scale to high dimensionality and rapidly filter unproductive pairwise comparison. Two bioinformatics applications of the tool are presented to demonstrate the ability to scale to billions of pairwise comparisons and the usefulness of this approach.« less

Energy Efficient Engine acoustic supporting technology report

NASA Technical Reports Server (NTRS)

Lavin, S. P.; Ho, P. Y.

1985-01-01

The acoustic development of the Energy Efficient Engine combined testing and analysis using scale model rigs and an integrated Core/Low Spool demonstration engine. The scale model tests show that a cut-on blade/vane ratio fan with a large spacing (S/C = 2.3) is as quiet as a cut-off blade/vane ratio with a tighter spacing (S/C = 1.27). Scale model mixer tests show that separate flow nozzles are the noisiest, conic nozzles the quietest, with forced mixers in between. Based on projections of ICLS data the Energy Efficient Engine (E3) has FAR 36 margins of 3.7 EPNdB at approach, 4.5 EPNdB at full power takeoff, and 7.2 EPNdB at sideline conditions.

Beyond Scale-Free Small-World Networks: Cortical Columns for Quick Brains

NASA Astrophysics Data System (ADS)

Stoop, Ralph; Saase, Victor; Wagner, Clemens; Stoop, Britta; Stoop, Ruedi

2013-03-01

We study to what extent cortical columns with their particular wiring boost neural computation. Upon a vast survey of columnar networks performing various real-world cognitive tasks, we detect no signs of enhancement. It is on a mesoscopic—intercolumnar—scale that the existence of columns, largely irrespective of their inner organization, enhances the speed of information transfer and minimizes the total wiring length required to bind distributed columnar computations towards spatiotemporally coherent results. We suggest that brain efficiency may be related to a doubly fractal connectivity law, resulting in networks with efficiency properties beyond those by scale-free networks.

Generating multi-photon W-like states for perfect quantum teleportation and superdense coding

NASA Astrophysics Data System (ADS)

Li, Ke; Kong, Fan-Zhen; Yang, Ming; Ozaydin, Fatih; Yang, Qing; Cao, Zhuo-Liang

2016-08-01

An interesting aspect of multipartite entanglement is that for perfect teleportation and superdense coding, not the maximally entangled W states but a special class of non-maximally entangled W-like states are required. Therefore, efficient preparation of such W-like states is of great importance in quantum communications, which has not been studied as much as the preparation of W states. In this paper, we propose a simple optical scheme for efficient preparation of large-scale polarization-based entangled W-like states by fusing two W-like states or expanding a W-like state with an ancilla photon. Our scheme can also generate large-scale W states by fusing or expanding W or even W-like states. The cost analysis shows that in generating large-scale W states, the fusion mechanism achieves a higher efficiency with non-maximally entangled W-like states than maximally entangled W states. Our scheme can also start fusion or expansion with Bell states, and it is composed of a polarization-dependent beam splitter, two polarizing beam splitters and photon detectors. Requiring no ancilla photon or controlled gate to operate, our scheme can be realized with the current photonics technology and we believe it enable advances in quantum teleportation and superdense coding in multipartite settings.

A novel combined SLAM based on RBPF-SLAM and EIF-SLAM for mobile system sensing in a large scale environment.

PubMed

He, Bo; Zhang, Shujing; Yan, Tianhong; Zhang, Tao; Liang, Yan; Zhang, Hongjin

2011-01-01

Mobile autonomous systems are very important for marine scientific investigation and military applications. Many algorithms have been studied to deal with the computational efficiency problem required for large scale simultaneous localization and mapping (SLAM) and its related accuracy and consistency. Among these methods, submap-based SLAM is a more effective one. By combining the strength of two popular mapping algorithms, the Rao-Blackwellised particle filter (RBPF) and extended information filter (EIF), this paper presents a combined SLAM-an efficient submap-based solution to the SLAM problem in a large scale environment. RBPF-SLAM is used to produce local maps, which are periodically fused into an EIF-SLAM algorithm. RBPF-SLAM can avoid linearization of the robot model during operating and provide a robust data association, while EIF-SLAM can improve the whole computational speed, and avoid the tendency of RBPF-SLAM to be over-confident. In order to further improve the computational speed in a real time environment, a binary-tree-based decision-making strategy is introduced. Simulation experiments show that the proposed combined SLAM algorithm significantly outperforms currently existing algorithms in terms of accuracy and consistency, as well as the computing efficiency. Finally, the combined SLAM algorithm is experimentally validated in a real environment by using the Victoria Park dataset.

Scaling and biomechanics of surface attachment in climbing animals

PubMed Central

Labonte, David; Federle, Walter

2015-01-01

Attachment devices are essential adaptations for climbing animals and valuable models for synthetic adhesives. A major unresolved question for both natural and bioinspired attachment systems is how attachment performance depends on size. Here, we discuss how contact geometry and mode of detachment influence the scaling of attachment forces for claws and adhesive pads, and how allometric data on biological systems can yield insights into their mechanism of attachment. Larger animals are expected to attach less well to surfaces, due to their smaller surface-to-volume ratio, and because it becomes increasingly difficult to distribute load uniformly across large contact areas. In order to compensate for this decrease of weight-specific adhesion, large animals could evolve overproportionally large pads, or adaptations that increase attachment efficiency (adhesion or friction per unit contact area). Available data suggest that attachment pad area scales close to isometry within clades, but pad efficiency in some animals increases with size so that attachment performance is approximately size-independent. The mechanisms underlying this biologically important variation in pad efficiency are still unclear. We suggest that switching between stress concentration (easy detachment) and uniform load distribution (strong attachment) via shear forces is one of the key mechanisms enabling the dynamic control of adhesion during locomotion. PMID:25533088

Implementing Parquet equations using HPX

NASA Astrophysics Data System (ADS)

Kellar, Samuel; Wagle, Bibek; Yang, Shuxiang; Tam, Ka-Ming; Kaiser, Hartmut; Moreno, Juana; Jarrell, Mark

A new C++ runtime system (HPX) enables simulations of complex systems to run more efficiently on parallel and heterogeneous systems. This increased efficiency allows for solutions to larger simulations of the parquet approximation for a system with impurities. The relevancy of the parquet equations depends upon the ability to solve systems which require long runs and large amounts of memory. These limitations, in addition to numerical complications arising from stability of the solutions, necessitate running on large distributed systems. As the computational resources trend towards the exascale and the limitations arising from computational resources vanish efficiency of large scale simulations becomes a focus. HPX facilitates efficient simulations through intelligent overlapping of computation and communication. Simulations such as the parquet equations which require the transfer of large amounts of data should benefit from HPX implementations. Supported by the the NSF EPSCoR Cooperative Agreement No. EPS-1003897 with additional support from the Louisiana Board of Regents.

Improved uniformity in high-performance organic photovoltaics enabled by (3-aminopropyl)triethoxysilane cathode functionalization.

PubMed

Luck, Kyle A; Shastry, Tejas A; Loser, Stephen; Ogien, Gabriel; Marks, Tobin J; Hersam, Mark C

2013-12-28

Organic photovoltaics have the potential to serve as lightweight, low-cost, mechanically flexible solar cells. However, losses in efficiency as laboratory cells are scaled up to the module level have to date impeded large scale deployment. Here, we report that a 3-aminopropyltriethoxysilane (APTES) cathode interfacial treatment significantly enhances performance reproducibility in inverted high-efficiency PTB7:PC71BM organic photovoltaic cells, as demonstrated by the fabrication of 100 APTES-treated devices versus 100 untreated controls. The APTES-treated devices achieve a power conversion efficiency of 8.08 ± 0.12% with histogram skewness of -0.291, whereas the untreated controls achieve 7.80 ± 0.26% with histogram skewness of -1.86. By substantially suppressing the interfacial origins of underperforming cells, the APTES treatment offers a pathway for fabricating large-area modules with high spatial performance uniformity.

Large scale nanoparticle screening for small molecule analysis in laser desorption ionization mass spectrometry

DOE PAGES

Yagnik, Gargey B.; Hansen, Rebecca L.; Korte, Andrew R.; ...

2016-08-30

Nanoparticles (NPs) have been suggested as efficient matrixes for small molecule profiling and imaging by laser-desorption ionization mass spectrometry (LDI-MS), but so far there has been no systematic study comparing different NPs in the analysis of various classes of small molecules. Here, we present a large scale screening of 13 NPs for the analysis of two dozen small metabolite molecules. Many NPs showed much higher LDI efficiency than organic matrixes in positive mode and some NPs showed comparable efficiencies for selected analytes in negative mode. Our results suggest that a thermally driven desorption process is a key factor for metalmore » oxide NPs, but chemical interactions are also very important, especially for other NPs. Furthermore, the screening results provide a useful guideline for the selection of NPs in the LDI-MS analysis of small molecules.« less

Large scale nanoparticle screening for small molecule analysis in laser desorption ionization mass spectrometry

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yagnik, Gargey B.; Hansen, Rebecca L.; Korte, Andrew R.

Nanoparticles (NPs) have been suggested as efficient matrixes for small molecule profiling and imaging by laser-desorption ionization mass spectrometry (LDI-MS), but so far there has been no systematic study comparing different NPs in the analysis of various classes of small molecules. Here, we present a large scale screening of 13 NPs for the analysis of two dozen small metabolite molecules. Many NPs showed much higher LDI efficiency than organic matrixes in positive mode and some NPs showed comparable efficiencies for selected analytes in negative mode. Our results suggest that a thermally driven desorption process is a key factor for metalmore » oxide NPs, but chemical interactions are also very important, especially for other NPs. Furthermore, the screening results provide a useful guideline for the selection of NPs in the LDI-MS analysis of small molecules.« less

Enhancing the transmission efficiency by edge deletion in scale-free networks

NASA Astrophysics Data System (ADS)

Zhang, Guo-Qing; Wang, Di; Li, Guo-Jie

2007-07-01

How to improve the transmission efficiency of Internet-like packet switching networks is one of the most important problems in complex networks as well as for the Internet research community. In this paper we propose a convenient method to enhance the transmission efficiency of scale-free networks dramatically by kicking out the edges linking to nodes with large betweenness, which we called the “black sheep.” The advantages of our method are of facility and practical importance. Since the black sheep edges are very costly due to their large bandwidth, our method could decrease the cost as well as gain higher throughput of networks. Moreover, we analyze the curve of the largest betweenness on deleting more and more black sheep edges and find that there is a sharp transition at the critical point where the average degree of the nodes ⟨k⟩→2 .

A family of conjugate gradient methods for large-scale nonlinear equations.

PubMed

Feng, Dexiang; Sun, Min; Wang, Xueyong

2017-01-01

In this paper, we present a family of conjugate gradient projection methods for solving large-scale nonlinear equations. At each iteration, it needs low storage and the subproblem can be easily solved. Compared with the existing solution methods for solving the problem, its global convergence is established without the restriction of the Lipschitz continuity on the underlying mapping. Preliminary numerical results are reported to show the efficiency of the proposed method.

Modelling the large-scale redshift-space 3-point correlation function of galaxies

NASA Astrophysics Data System (ADS)

Slepian, Zachary; Eisenstein, Daniel J.

2017-08-01

We present a configuration-space model of the large-scale galaxy 3-point correlation function (3PCF) based on leading-order perturbation theory and including redshift-space distortions (RSD). This model should be useful in extracting distance-scale information from the 3PCF via the baryon acoustic oscillation method. We include the first redshift-space treatment of biasing by the baryon-dark matter relative velocity. Overall, on large scales the effect of RSD is primarily a renormalization of the 3PCF that is roughly independent of both physical scale and triangle opening angle; for our adopted Ωm and bias values, the rescaling is a factor of ˜1.8. We also present an efficient scheme for computing 3PCF predictions from our model, important for allowing fast exploration of the space of cosmological parameters in future analyses.

Small-scale test program to develop a more efficient swivel nozzle thrust deflector for V/STOL lift/cruise engines

NASA Technical Reports Server (NTRS)

Schlundt, D. W.

1976-01-01

The installed performance degradation of a swivel nozzle thrust deflector system obtained during increased vectoring angles of a large-scale test program was investigated and improved. Small-scale models were used to generate performance data for analyzing selected swivel nozzle configurations. A single-swivel nozzle design model with five different nozzle configurations and a twin-swivel nozzle design model, scaled to 0.15 size of the large-scale test hardware, were statically tested at low exhaust pressure ratios of 1.4, 1.3, 1.2, and 1.1 and vectored at four nozzle positions from 0 deg cruise through 90 deg vertical used for the VTOL mode.

Assessing the weighted multi-objective adaptive surrogate model optimization to derive large-scale reservoir operating rules with sensitivity analysis

NASA Astrophysics Data System (ADS)

Zhang, Jingwen; Wang, Xu; Liu, Pan; Lei, Xiaohui; Li, Zejun; Gong, Wei; Duan, Qingyun; Wang, Hao

2017-01-01

The optimization of large-scale reservoir system is time-consuming due to its intrinsic characteristics of non-commensurable objectives and high dimensionality. One way to solve the problem is to employ an efficient multi-objective optimization algorithm in the derivation of large-scale reservoir operating rules. In this study, the Weighted Multi-Objective Adaptive Surrogate Model Optimization (WMO-ASMO) algorithm is used. It consists of three steps: (1) simplifying the large-scale reservoir operating rules by the aggregation-decomposition model, (2) identifying the most sensitive parameters through multivariate adaptive regression splines (MARS) for dimensional reduction, and (3) reducing computational cost and speeding the searching process by WMO-ASMO, embedded with weighted non-dominated sorting genetic algorithm II (WNSGAII). The intercomparison of non-dominated sorting genetic algorithm (NSGAII), WNSGAII and WMO-ASMO are conducted in the large-scale reservoir system of Xijiang river basin in China. Results indicate that: (1) WNSGAII surpasses NSGAII in the median of annual power generation, increased by 1.03% (from 523.29 to 528.67 billion kW h), and the median of ecological index, optimized by 3.87% (from 1.879 to 1.809) with 500 simulations, because of the weighted crowding distance and (2) WMO-ASMO outperforms NSGAII and WNSGAII in terms of better solutions (annual power generation (530.032 billion kW h) and ecological index (1.675)) with 1000 simulations and computational time reduced by 25% (from 10 h to 8 h) with 500 simulations. Therefore, the proposed method is proved to be more efficient and could provide better Pareto frontier.

Development of a database system for mapping insertional mutations onto the mouse genome with large-scale experimental data

PubMed Central

2009-01-01

Background Insertional mutagenesis is an effective method for functional genomic studies in various organisms. It can rapidly generate easily tractable mutations. A large-scale insertional mutagenesis with the piggyBac (PB) transposon is currently performed in mice at the Institute of Developmental Biology and Molecular Medicine (IDM), Fudan University in Shanghai, China. This project is carried out via collaborations among multiple groups overseeing interconnected experimental steps and generates a large volume of experimental data continuously. Therefore, the project calls for an efficient database system for recording, management, statistical analysis, and information exchange. Results This paper presents a database application called MP-PBmice (insertional mutation mapping system of PB Mutagenesis Information Center), which is developed to serve the on-going large-scale PB insertional mutagenesis project. A lightweight enterprise-level development framework Struts-Spring-Hibernate is used here to ensure constructive and flexible support to the application. The MP-PBmice database system has three major features: strict access-control, efficient workflow control, and good expandability. It supports the collaboration among different groups that enter data and exchange information on daily basis, and is capable of providing real time progress reports for the whole project. MP-PBmice can be easily adapted for other large-scale insertional mutation mapping projects and the source code of this software is freely available at http://www.idmshanghai.cn/PBmice. Conclusion MP-PBmice is a web-based application for large-scale insertional mutation mapping onto the mouse genome, implemented with the widely used framework Struts-Spring-Hibernate. This system is already in use by the on-going genome-wide PB insertional mutation mapping project at IDM, Fudan University. PMID:19958505

Falcon: Visual analysis of large, irregularly sampled, and multivariate time series data in additive manufacturing

DOE PAGES

Steed, Chad A.; Halsey, William; Dehoff, Ryan; ...

2017-02-16

Flexible visual analysis of long, high-resolution, and irregularly sampled time series data from multiple sensor streams is a challenge in several domains. In the field of additive manufacturing, this capability is critical for realizing the full potential of large-scale 3D printers. Here, we propose a visual analytics approach that helps additive manufacturing researchers acquire a deep understanding of patterns in log and imagery data collected by 3D printers. Our specific goals include discovering patterns related to defects and system performance issues, optimizing build configurations to avoid defects, and increasing production efficiency. We introduce Falcon, a new visual analytics system thatmore » allows users to interactively explore large, time-oriented data sets from multiple linked perspectives. Falcon provides overviews, detailed views, and unique segmented time series visualizations, all with adjustable scale options. To illustrate the effectiveness of Falcon at providing thorough and efficient knowledge discovery, we present a practical case study involving experts in additive manufacturing and data from a large-scale 3D printer. The techniques described are applicable to the analysis of any quantitative time series, though the focus of this paper is on additive manufacturing.« less

Falcon: Visual analysis of large, irregularly sampled, and multivariate time series data in additive manufacturing

DOE Office of Scientific and Technical Information (OSTI.GOV)

Steed, Chad A.; Halsey, William; Dehoff, Ryan

Flexible visual analysis of long, high-resolution, and irregularly sampled time series data from multiple sensor streams is a challenge in several domains. In the field of additive manufacturing, this capability is critical for realizing the full potential of large-scale 3D printers. Here, we propose a visual analytics approach that helps additive manufacturing researchers acquire a deep understanding of patterns in log and imagery data collected by 3D printers. Our specific goals include discovering patterns related to defects and system performance issues, optimizing build configurations to avoid defects, and increasing production efficiency. We introduce Falcon, a new visual analytics system thatmore » allows users to interactively explore large, time-oriented data sets from multiple linked perspectives. Falcon provides overviews, detailed views, and unique segmented time series visualizations, all with adjustable scale options. To illustrate the effectiveness of Falcon at providing thorough and efficient knowledge discovery, we present a practical case study involving experts in additive manufacturing and data from a large-scale 3D printer. The techniques described are applicable to the analysis of any quantitative time series, though the focus of this paper is on additive manufacturing.« less

A forward-advancing wave expansion method for numerical solution of large-scale sound propagation problems

NASA Astrophysics Data System (ADS)

Rolla, L. Barrera; Rice, H. J.

2006-09-01

In this paper a "forward-advancing" field discretization method suitable for solving the Helmholtz equation in large-scale problems is proposed. The forward wave expansion method (FWEM) is derived from a highly efficient discretization procedure based on interpolation of wave functions known as the wave expansion method (WEM). The FWEM computes the propagated sound field by means of an exclusively forward advancing solution, neglecting the backscattered field. It is thus analogous to methods such as the (one way) parabolic equation method (PEM) (usually discretized using standard finite difference or finite element methods). These techniques do not require the inversion of large system matrices and thus enable the solution of large-scale acoustic problems where backscatter is not of interest. Calculations using FWEM are presented for two propagation problems and comparisons to data computed with analytical and theoretical solutions and show this forward approximation to be highly accurate. Examples of sound propagation over a screen in upwind and downwind refracting atmospheric conditions at low nodal spacings (0.2 per wavelength in the propagation direction) are also included to demonstrate the flexibility and efficiency of the method.

Improving efficiency of polystyrene concrete production with composite binders

NASA Astrophysics Data System (ADS)

Lesovik, R. V.; Ageeva, M. S.; Lesovik, G. A.; Sopin, D. M.; Kazlitina, O. V.; Mitrokhina, A. A.

2018-03-01

According to leading marketing researchers, the construction market in Russia and CIS will continue growing at a rapid rate; this applies not only to a large-scale major construction, but to a construction of single-family houses and small-scale industrial facilities as well. Due to this, there are increased requirements for heat insulation of the building enclosures and a significant demand for efficient walling materials with high thermal performance. All these developments led to higher requirements imposed on the equipment that produces such materials.

Reducing computational costs in large scale 3D EIT by using a sparse Jacobian matrix with block-wise CGLS reconstruction.

PubMed

Yang, C L; Wei, H Y; Adler, A; Soleimani, M

2013-06-01

Electrical impedance tomography (EIT) is a fast and cost-effective technique to provide a tomographic conductivity image of a subject from boundary current-voltage data. This paper proposes a time and memory efficient method for solving a large scale 3D EIT inverse problem using a parallel conjugate gradient (CG) algorithm. The 3D EIT system with a large number of measurement data can produce a large size of Jacobian matrix; this could cause difficulties in computer storage and the inversion process. One of challenges in 3D EIT is to decrease the reconstruction time and memory usage, at the same time retaining the image quality. Firstly, a sparse matrix reduction technique is proposed using thresholding to set very small values of the Jacobian matrix to zero. By adjusting the Jacobian matrix into a sparse format, the element with zeros would be eliminated, which results in a saving of memory requirement. Secondly, a block-wise CG method for parallel reconstruction has been developed. The proposed method has been tested using simulated data as well as experimental test samples. Sparse Jacobian with a block-wise CG enables the large scale EIT problem to be solved efficiently. Image quality measures are presented to quantify the effect of sparse matrix reduction in reconstruction results.

Accuracy improvement in laser stripe extraction for large-scale triangulation scanning measurement system

NASA Astrophysics Data System (ADS)

Zhang, Yang; Liu, Wei; Li, Xiaodong; Yang, Fan; Gao, Peng; Jia, Zhenyuan

2015-10-01

Large-scale triangulation scanning measurement systems are widely used to measure the three-dimensional profile of large-scale components and parts. The accuracy and speed of the laser stripe center extraction are essential for guaranteeing the accuracy and efficiency of the measuring system. However, in the process of large-scale measurement, multiple factors can cause deviation of the laser stripe center, including the spatial light intensity distribution, material reflectivity characteristics, and spatial transmission characteristics. A center extraction method is proposed for improving the accuracy of the laser stripe center extraction based on image evaluation of Gaussian fitting structural similarity and analysis of the multiple source factors. First, according to the features of the gray distribution of the laser stripe, evaluation of the Gaussian fitting structural similarity is estimated to provide a threshold value for center compensation. Then using the relationships between the gray distribution of the laser stripe and the multiple source factors, a compensation method of center extraction is presented. Finally, measurement experiments for a large-scale aviation composite component are carried out. The experimental results for this specific implementation verify the feasibility of the proposed center extraction method and the improved accuracy for large-scale triangulation scanning measurements.

Agricultural Inputs and Efficiency in Tanzania Small Scale Agriculture: A Comparative Analysis of Tobacco and Selected Food Crops

PubMed Central

Kidane, A.; Hepelwa, A.; Tingum, E.; Hu, T.W.

2016-01-01

In this study an attempt is made to compare the efficiency in tobacco leaf production with three other cereals – maize, ground nut and rice – commonly grown by Tanzanian small scale farmers. The paper reviews the prevalence of tobacco use in Africa with that of the developed world; while there was a decline in the latter there appears to be an increase in the former. The economic benefit and costs of tobacco production and consumption in Tanzania are also compared. Using a nationally representative large scale data we were able to observe that modern agricultural inputs allotted to tobacco was much higher than those allotted to maize, ground nut and rice. Using A Frontier Production approach, the study shows that the efficiency of tobacco, maize, groundnuts and rice were 75.3%, 68.5%, 64.5% and 46.5% respectively. Despite the infusion of massive agricultural input allotted to it, tobacco is still 75.3% efficient-tobacco farmers should have produced the same amount by utilizing only 75.3% of realized inputs. The relatively high efficiency in tobacco can only be explained by the large scale allocation of modern agricultural inputs such as fertilizer, better seeds, credit facility and easy access to market. The situation is likely to be reversed if more allocation of inputs were directed to basic food crops such as maize, rice and ground nuts. Tanzania’s policy of food security and poverty alleviation can only be achieved by allocating more modern inputs to basic necessities such as maize and rice. PMID:28124032

A solvent- and vacuum-free route to large-area perovskite films for efficient solar modules

NASA Astrophysics Data System (ADS)

Chen, Han; Ye, Fei; Tang, Wentao; He, Jinjin; Yin, Maoshu; Wang, Yanbo; Xie, Fengxian; Bi, Enbing; Yang, Xudong; Grätzel, Michael; Han, Liyuan

2017-10-01

Recent advances in the use of organic-inorganic hybrid perovskites for optoelectronics have been rapid, with reported power conversion efficiencies of up to 22 per cent for perovskite solar cells. Improvements in stability have also enabled testing over a timescale of thousands of hours. However, large-scale deployment of such cells will also require the ability to produce large-area, uniformly high-quality perovskite films. A key challenge is to overcome the substantial reduction in power conversion efficiency when a small device is scaled up: a reduction from over 20 per cent to about 10 per cent is found when a common aperture area of about 0.1 square centimetres is increased to more than 25 square centimetres. Here we report a new deposition route for methyl ammonium lead halide perovskite films that does not rely on use of a common solvent or vacuum: rather, it relies on the rapid conversion of amine complex precursors to perovskite films, followed by a pressure application step. The deposited perovskite films were free of pin-holes and highly uniform. Importantly, the new deposition approach can be performed in air at low temperatures, facilitating fabrication of large-area perovskite devices. We reached a certified power conversion efficiency of 12.1 per cent with an aperture area of 36.1 square centimetres for a mesoporous TiO2-based perovskite solar module architecture.

Electrodeposition of hierarchically structured three-dimensional nickel–iron electrodes for efficient oxygen evolution at high current densities

PubMed Central

Lu, Xunyu; Zhao, Chuan

2015-01-01

Large-scale industrial application of electrolytic splitting of water has called for the development of oxygen evolution electrodes that are inexpensive, robust and can deliver large current density (>500 mA cm−2) at low applied potentials. Here we show that an efficient oxygen electrode can be developed by electrodepositing amorphous mesoporous nickel–iron composite nanosheets directly onto macroporous nickel foam substrates. The as-prepared oxygen electrode exhibits high catalytic activity towards water oxidation in alkaline solutions, which only requires an overpotential of 200 mV to initiate the reaction, and is capable of delivering current densities of 500 and 1,000 mA cm−2 at overpotentials of 240 and 270 mV, respectively. The electrode also shows prolonged stability against bulk water electrolysis at large current. Collectively, the as-prepared three-dimensional structured electrode is the most efficient oxygen evolution electrode in alkaline electrolytes reported to the best of our knowledge, and can potentially be applied for industrial scale water electrolysis. PMID:25776015

Towards building high performance medical image management system for clinical trials

NASA Astrophysics Data System (ADS)

Wang, Fusheng; Lee, Rubao; Zhang, Xiaodong; Saltz, Joel

2011-03-01

Medical image based biomarkers are being established for therapeutic cancer clinical trials, where image assessment is among the essential tasks. Large scale image assessment is often performed by a large group of experts by retrieving images from a centralized image repository to workstations to markup and annotate images. In such environment, it is critical to provide a high performance image management system that supports efficient concurrent image retrievals in a distributed environment. There are several major challenges: high throughput of large scale image data over the Internet from the server for multiple concurrent client users, efficient communication protocols for transporting data, and effective management of versioning of data for audit trails. We study the major bottlenecks for such a system, propose and evaluate a solution by using a hybrid image storage with solid state drives and hard disk drives, RESTfulWeb Services based protocols for exchanging image data, and a database based versioning scheme for efficient archive of image revision history. Our experiments show promising results of our methods, and our work provides a guideline for building enterprise level high performance medical image management systems.

Modulation-doped growth of mosaic graphene with single-crystalline p–n junctions for efficient photocurrent generation

PubMed Central

Yan, Kai; Wu, Di; Peng, Hailin; Jin, Li; Fu, Qiang; Bao, Xinhe; Liu, Zhongfan

2012-01-01

Device applications of graphene such as ultrafast transistors and photodetectors benefit from the combination of both high-quality p- and n-doped components prepared in a large-scale manner with spatial control and seamless connection. Here we develop a well-controlled chemical vapour deposition process for direct growth of mosaic graphene. Mosaic graphene is produced in large-area monolayers with spatially modulated, stable and uniform doping, and shows considerably high room temperature carrier mobility of ~5,000 cm2 V−1 s−1 in intrinsic portion and ~2,500 cm2 V−1 s−1 in nitrogen-doped portion. The unchanged crystalline registry during modulation doping indicates the single-crystalline nature of p–n junctions. Efficient hot carrier-assisted photocurrent was generated by laser excitation at the junction under ambient conditions. This study provides a facile avenue for large-scale synthesis of single-crystalline graphene p–n junctions, allowing for batch fabrication and integration of high-efficiency optoelectronic and electronic devices within the atomically thin film. PMID:23232410

Linear static structural and vibration analysis on high-performance computers

NASA Technical Reports Server (NTRS)

Baddourah, M. A.; Storaasli, O. O.; Bostic, S. W.

1993-01-01

Parallel computers offer the oppurtunity to significantly reduce the computation time necessary to analyze large-scale aerospace structures. This paper presents algorithms developed for and implemented on massively-parallel computers hereafter referred to as Scalable High-Performance Computers (SHPC), for the most computationally intensive tasks involved in structural analysis, namely, generation and assembly of system matrices, solution of systems of equations and calculation of the eigenvalues and eigenvectors. Results on SHPC are presented for large-scale structural problems (i.e. models for High-Speed Civil Transport). The goal of this research is to develop a new, efficient technique which extends structural analysis to SHPC and makes large-scale structural analyses tractable.

Review of Dynamic Modeling and Simulation of Large Scale Belt Conveyor System

NASA Astrophysics Data System (ADS)

He, Qing; Li, Hong

Belt conveyor is one of the most important devices to transport bulk-solid material for long distance. Dynamic analysis is the key to decide whether the design is rational in technique, safe and reliable in running, feasible in economy. It is very important to study dynamic properties, improve efficiency and productivity, guarantee conveyor safe, reliable and stable running. The dynamic researches and applications of large scale belt conveyor are discussed. The main research topics, the state-of-the-art of dynamic researches on belt conveyor are analyzed. The main future works focus on dynamic analysis, modeling and simulation of main components and whole system, nonlinear modeling, simulation and vibration analysis of large scale conveyor system.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gallarno, George; Rogers, James H; Maxwell, Don E

The high computational capability of graphics processing units (GPUs) is enabling and driving the scientific discovery process at large-scale. The world s second fastest supercomputer for open science, Titan, has more than 18,000 GPUs that computational scientists use to perform scientific simu- lations and data analysis. Understanding of GPU reliability characteristics, however, is still in its nascent stage since GPUs have only recently been deployed at large-scale. This paper presents a detailed study of GPU errors and their impact on system operations and applications, describing experiences with the 18,688 GPUs on the Titan supercom- puter as well as lessons learnedmore » in the process of efficient operation of GPUs at scale. These experiences are helpful to HPC sites which already have large-scale GPU clusters or plan to deploy GPUs in the future.« less

Towards high efficiency heliostat fields

NASA Astrophysics Data System (ADS)

Arbes, Florian; Wöhrbach, Markus; Gebreiter, Daniel; Weinrebe, Gerhard

2017-06-01

CSP power plants have great potential to substantially contribute to world energy supply. To set this free, cost reductions are required for future projects. Heliostat field layout optimization offers a great opportunity to improve field efficiency. Field efficiency primarily depends on the positions of the heliostats around the tower, commonly known as the heliostat field layout. Heliostat shape also influences efficiency. Improvements to optical efficiency results in electricity cost reduction without adding any extra technical complexity. Due to computational challenges heliostat fields are often arranged in patterns. The mathematical models of the radial staggered or spiral patterns are based on two parameters and thus lead to uniform patterns. Optical efficiencies of a heliostat field do not change uniformly with the distance to the tower, they even differ in the northern and southern field. A fixed pattern is not optimal in many parts of the heliostat field, especially when used as large scaled heliostat field. In this paper, two methods are described which allow to modify field density suitable to inconsistent field efficiencies. A new software for large scale heliostat field evaluation is presented, it allows for fast optimizations of several parameters for pattern modification routines. It was used to design a heliostat field with 23,000 heliostats, which is currently planned for a site in South Africa.

Research on the impacts of large-scale electric vehicles integration into power grid

NASA Astrophysics Data System (ADS)

Su, Chuankun; Zhang, Jian

2018-06-01

Because of its special energy driving mode, electric vehicles can improve the efficiency of energy utilization and reduce the pollution to the environment, which is being paid more and more attention. But the charging behavior of electric vehicles is random and intermittent. If the electric vehicle is disordered charging in a large scale, it causes great pressure on the structure and operation of the power grid and affects the safety and economic operation of the power grid. With the development of V2G technology in electric vehicle, the study of the charging and discharging characteristics of electric vehicles is of great significance for improving the safe operation of the power grid and the efficiency of energy utilization.

Efficient tiled calculation of over-10-gigapixel holograms using ray-wavefront conversion.

PubMed

Igarashi, Shunsuke; Nakamura, Tomoya; Matsushima, Kyoji; Yamaguchi, Masahiro

2018-04-16

In the calculation of large-scale computer-generated holograms, an approach called "tiling," which divides the hologram plane into small rectangles, is often employed due to limitations on computational memory. However, the total amount of computational complexity severely increases with the number of divisions. In this paper, we propose an efficient method for calculating tiled large-scale holograms using ray-wavefront conversion. In experiments, the effectiveness of the proposed method was verified by comparing its calculation cost with that using the previous method. Additionally, a hologram of 128K × 128K pixels was calculated and fabricated by a laser-lithography system, and a high-quality 105 mm × 105 mm 3D image including complicated reflection and translucency was optically reconstructed.

A Low Collision and High Throughput Data Collection Mechanism for Large-Scale Super Dense Wireless Sensor Networks.

PubMed

Lei, Chunyang; Bie, Hongxia; Fang, Gengfa; Gaura, Elena; Brusey, James; Zhang, Xuekun; Dutkiewicz, Eryk

2016-07-18

Super dense wireless sensor networks (WSNs) have become popular with the development of Internet of Things (IoT), Machine-to-Machine (M2M) communications and Vehicular-to-Vehicular (V2V) networks. While highly-dense wireless networks provide efficient and sustainable solutions to collect precise environmental information, a new channel access scheme is needed to solve the channel collision problem caused by the large number of competing nodes accessing the channel simultaneously. In this paper, we propose a space-time random access method based on a directional data transmission strategy, by which collisions in the wireless channel are significantly decreased and channel utility efficiency is greatly enhanced. Simulation results show that our proposed method can decrease the packet loss rate to less than 2 % in large scale WSNs and in comparison with other channel access schemes for WSNs, the average network throughput can be doubled.

Large-area, lightweight and thick biomimetic composites with superior material properties via fast, economic, and green pathways.

PubMed

Walther, Andreas; Bjurhager, Ingela; Malho, Jani-Markus; Pere, Jaakko; Ruokolainen, Janne; Berglund, Lars A; Ikkala, Olli

2010-08-11

Although remarkable success has been achieved to mimic the mechanically excellent structure of nacre in laboratory-scale models, it remains difficult to foresee mainstream applications due to time-consuming sequential depositions or energy-intensive processes. Here, we introduce a surprisingly simple and rapid methodology for large-area, lightweight, and thick nacre-mimetic films and laminates with superior material properties. Nanoclay sheets with soft polymer coatings are used as ideal building blocks with intrinsic hard/soft character. They are forced to rapidly self-assemble into aligned nacre-mimetic films via paper-making, doctor-blading or simple painting, giving rise to strong and thick films with tensile modulus of 45 GPa and strength of 250 MPa, that is, partly exceeding nacre. The concepts are environmentally friendly, energy-efficient, and economic and are ready for scale-up via continuous roll-to-roll processes. Excellent gas barrier properties, optical translucency, and extraordinary shape-persistent fire-resistance are demonstrated. We foresee advanced large-scale biomimetic materials, relevant for lightweight sustainable construction and energy-efficient transportation.

Green Routing Fuel Saving Opportunity Assessment: A Case Study on California Large-Scale Real-World Travel Data: Preprint

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhu, Lei; Holden, Jacob; Gonder, Jeff

New technologies, such as connected and automated vehicles, have attracted more and more researchers for improving the energy efficiency and environmental impact of current transportation systems. The green routing strategy instructs a vehicle to select the most fuel-efficient route before the vehicle departs. It benefits the current transportation system with fuel saving opportunity through identifying the greenest route. This paper introduces an evaluation framework for estimating benefits of green routing based on large-scale, real-world travel data. The framework has the capability to quantify fuel savings by estimating the fuel consumption of actual routes and comparing to routes procured by navigationmore » systems. A route-based fuel consumption estimation model, considering road traffic conditions, functional class, and road grade is proposed and used in the framework. An experiment using a large-scale data set from the California Household Travel Survey global positioning system trajectory data base indicates that 31% of actual routes have fuel savings potential with a cumulative estimated fuel savings of 12%.« less

Green Routing Fuel Saving Opportunity Assessment: A Case Study on California Large-Scale Real-World Travel Data

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhu, Lei; Holden, Jacob; Gonder, Jeffrey D

New technologies, such as connected and automated vehicles, have attracted more and more researchers for improving the energy efficiency and environmental impact of current transportation systems. The green routing strategy instructs a vehicle to select the most fuel-efficient route before the vehicle departs. It benefits the current transportation system with fuel saving opportunity through identifying the greenest route. This paper introduces an evaluation framework for estimating benefits of green routing based on large-scale, real-world travel data. The framework has the capability to quantify fuel savings by estimating the fuel consumption of actual routes and comparing to routes procured by navigationmore » systems. A route-based fuel consumption estimation model, considering road traffic conditions, functional class, and road grade is proposed and used in the framework. An experiment using a large-scale data set from the California Household Travel Survey global positioning system trajectory data base indicates that 31% of actual routes have fuel savings potential with a cumulative estimated fuel savings of 12%.« less

Design of coated standing nanowire array solar cell performing beyond the planar efficiency limits

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zeng, Yang; Ye, Qinghao; Shen, Wenzhong, E-mail: wzshen@sjtu.edu.cn

2016-05-28

The single standing nanowire (SNW) solar cells have been proven to perform beyond the planar efficiency limits in both open-circuit voltage and internal quantum efficiency due to the built-in concentration and the shifting of the absorption front. However, the expandability of these nano-scale units to a macro-scale photovoltaic device remains unsolved. The main difficulty lies in the simultaneous preservation of an effective built-in concentration in each unit cell and a broadband high absorption capability of their array. Here, we have provided a detailed theoretical guideline for realizing a macro-scale solar cell that performs furthest beyond the planar limits. The keymore » lies in a complementary design between the light-trapping of the single SNWs and that of the photonic crystal slab formed by the array. By tuning the hybrid HE modes of the SNWs through the thickness of a coaxial dielectric coating, the optimized coated SNW array can sustain an absorption rate over 97.5% for a period as large as 425 nm, which, together with the inherited carrier extraction advantage, leads to a cell efficiency increment of 30% over the planar limit. This work has demonstrated the viability of a large-size solar cell that performs beyond the planar limits.« less

A k-space method for large-scale models of wave propagation in tissue.

PubMed

Mast, T D; Souriau, L P; Liu, D L; Tabei, M; Nachman, A I; Waag, R C

2001-03-01

Large-scale simulation of ultrasonic pulse propagation in inhomogeneous tissue is important for the study of ultrasound-tissue interaction as well as for development of new imaging methods. Typical scales of interest span hundreds of wavelengths; most current two-dimensional methods, such as finite-difference and finite-element methods, are unable to compute propagation on this scale with the efficiency needed for imaging studies. Furthermore, for most available methods of simulating ultrasonic propagation, large-scale, three-dimensional computations of ultrasonic scattering are infeasible. Some of these difficulties have been overcome by previous pseudospectral and k-space methods, which allow substantial portions of the necessary computations to be executed using fast Fourier transforms. This paper presents a simplified derivation of the k-space method for a medium of variable sound speed and density; the derivation clearly shows the relationship of this k-space method to both past k-space methods and pseudospectral methods. In the present method, the spatial differential equations are solved by a simple Fourier transform method, and temporal iteration is performed using a k-t space propagator. The temporal iteration procedure is shown to be exact for homogeneous media, unconditionally stable for "slow" (c(x) < or = c0) media, and highly accurate for general weakly scattering media. The applicability of the k-space method to large-scale soft tissue modeling is shown by simulating two-dimensional propagation of an incident plane wave through several tissue-mimicking cylinders as well as a model chest wall cross section. A three-dimensional implementation of the k-space method is also employed for the example problem of propagation through a tissue-mimicking sphere. Numerical results indicate that the k-space method is accurate for large-scale soft tissue computations with much greater efficiency than that of an analogous leapfrog pseudospectral method or a 2-4 finite difference time-domain method. However, numerical results also indicate that the k-space method is less accurate than the finite-difference method for a high contrast scatterer with bone-like properties, although qualitative results can still be obtained by the k-space method with high efficiency. Possible extensions to the method, including representation of absorption effects, absorbing boundary conditions, elastic-wave propagation, and acoustic nonlinearity, are discussed.

Edge-SIFT: discriminative binary descriptor for scalable partial-duplicate mobile search.

PubMed

Zhang, Shiliang; Tian, Qi; Lu, Ke; Huang, Qingming; Gao, Wen

2013-07-01

As the basis of large-scale partial duplicate visual search on mobile devices, image local descriptor is expected to be discriminative, efficient, and compact. Our study shows that the popularly used histogram-based descriptors, such as scale invariant feature transform (SIFT) are not optimal for this task. This is mainly because histogram representation is relatively expensive to compute on mobile platforms and loses significant spatial clues, which are important for improving discriminative power and matching near-duplicate image patches. To address these issues, we propose to extract a novel binary local descriptor named Edge-SIFT from the binary edge maps of scale- and orientation-normalized image patches. By preserving both locations and orientations of edges and compressing the sparse binary edge maps with a boosting strategy, the final Edge-SIFT shows strong discriminative power with compact representation. Furthermore, we propose a fast similarity measurement and an indexing framework with flexible online verification. Hence, the Edge-SIFT allows an accurate and efficient image search and is ideal for computation sensitive scenarios such as a mobile image search. Experiments on a large-scale dataset manifest that the Edge-SIFT shows superior retrieval accuracy to Oriented BRIEF (ORB) and is superior to SIFT in the aspects of retrieval precision, efficiency, compactness, and transmission cost.

A feasibility study of large-scale photobiological hydrogen production utilizing mariculture-raised cyanobacteria.

PubMed

Sakurai, Hidehiro; Masukawa, Hajime; Kitashima, Masaharu; Inoue, Kazuhito

2010-01-01

In order to decrease CO(2) emissions from the burning of fossil fuels, the development of new renewable energy sources sufficiently large in quantity is essential. To meet this need, we propose large-scale H(2) production on the sea surface utilizing cyanobacteria. Although many of the relevant technologies are in the early stage of development, this chapter briefly examines the feasibility of such H(2) production, in order to illustrate that under certain conditions large-scale photobiological H(2) production can be viable. Assuming that solar energy is converted to H(2) at 1.2% efficiency, the future cost of H(2) can be estimated to be about 11 (pipelines) and 26.4 (compression and marine transportation) cents kWh(-1), respectively.

Use of Second Generation Coated Conductors for Efficient Shielding of dc Magnetic Fields (Postprint)

DTIC Science & Technology

2010-07-15

layer of superconducting film, can attenuate an external magnetic field of up to 5 mT by more than an order of magnitude. For comparison purposes...appears to be especially promising for the realization of large scale high-Tc superconducting screens. 15. SUBJECT TERMS magnetic screens, current...realization of large scale high-Tc superconducting screens. © 2010 American Institute of Physics. doi:10.1063/1.3459895 I. INTRODUCTION Magnetic screening

Large-scale broadband absorber based on metallic tungsten nanocone structure

NASA Astrophysics Data System (ADS)

Wang, Jiaxing; Liang, Yuzhang; Huo, Pengcheng; Wang, Daopeng; Tan, Jun; Xu, Ting

2017-12-01

We report a broadband tungsten absorber based on a nanocone metallic resonant structure fabricated by self-assembly nanosphere lithography. In experimental demonstration, the fabricated absorber has more than 90% average absorption efficiency and shows superior angular tolerance in the entire visible and near-infrared spectral region. We envision that this large-scale nanostructured broadband optical absorber would find great potential in the applications of high performance optoelectronic platforms and solar-thermal energy harvesting systems.

Efficient and Extensible Quasi-Explicit Modular Nonlinear Multiscale Battery Model: GH-MSMD

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kim, Gi-Heon; Smith, Kandler; Lawrence-Simon, Jake

Complex physics and long computation time hinder the adoption of computer aided engineering models in the design of large-format battery cells and systems. A modular, efficient battery simulation model -- the multiscale multidomain (MSMD) model -- was previously introduced to aid the scale-up of Li-ion material and electrode designs to complete cell and pack designs, capturing electrochemical interplay with 3-D electronic current pathways and thermal response. Here, this paper enhances the computational efficiency of the MSMD model using a separation of time-scales principle to decompose model field variables. The decomposition provides a quasi-explicit linkage between the multiple length-scale domains andmore » thus reduces time-consuming nested iteration when solving model equations across multiple domains. In addition to particle-, electrode- and cell-length scales treated in the previous work, the present formulation extends to bus bar- and multi-cell module-length scales. We provide example simulations for several variants of GH electrode-domain models.« less

Efficient and Extensible Quasi-Explicit Modular Nonlinear Multiscale Battery Model: GH-MSMD

DOE PAGES

Kim, Gi-Heon; Smith, Kandler; Lawrence-Simon, Jake; ...

2017-03-24

Complex physics and long computation time hinder the adoption of computer aided engineering models in the design of large-format battery cells and systems. A modular, efficient battery simulation model -- the multiscale multidomain (MSMD) model -- was previously introduced to aid the scale-up of Li-ion material and electrode designs to complete cell and pack designs, capturing electrochemical interplay with 3-D electronic current pathways and thermal response. Here, this paper enhances the computational efficiency of the MSMD model using a separation of time-scales principle to decompose model field variables. The decomposition provides a quasi-explicit linkage between the multiple length-scale domains andmore » thus reduces time-consuming nested iteration when solving model equations across multiple domains. In addition to particle-, electrode- and cell-length scales treated in the previous work, the present formulation extends to bus bar- and multi-cell module-length scales. We provide example simulations for several variants of GH electrode-domain models.« less

Towards Development of Clustering Applications for Large-Scale Comparative Genotyping and Kinship Analysis Using Y-Short Tandem Repeats.

PubMed

Seman, Ali; Sapawi, Azizian Mohd; Salleh, Mohd Zaki

2015-06-01

Y-chromosome short tandem repeats (Y-STRs) are genetic markers with practical applications in human identification. However, where mass identification is required (e.g., in the aftermath of disasters with significant fatalities), the efficiency of the process could be improved with new statistical approaches. Clustering applications are relatively new tools for large-scale comparative genotyping, and the k-Approximate Modal Haplotype (k-AMH), an efficient algorithm for clustering large-scale Y-STR data, represents a promising method for developing these tools. In this study we improved the k-AMH and produced three new algorithms: the Nk-AMH I (including a new initial cluster center selection), the Nk-AMH II (including a new dominant weighting value), and the Nk-AMH III (combining I and II). The Nk-AMH III was the superior algorithm, with mean clustering accuracy that increased in four out of six datasets and remained at 100% in the other two. Additionally, the Nk-AMH III achieved a 2% higher overall mean clustering accuracy score than the k-AMH, as well as optimal accuracy for all datasets (0.84-1.00). With inclusion of the two new methods, the Nk-AMH III produced an optimal solution for clustering Y-STR data; thus, the algorithm has potential for further development towards fully automatic clustering of any large-scale genotypic data.

Generalized Chirp Scaling Combined with Baseband Azimuth Scaling Algorithm for Large Bandwidth Sliding Spotlight SAR Imaging

PubMed Central

Yi, Tianzhu; He, Zhihua; He, Feng; Dong, Zhen; Wu, Manqing

2017-01-01

This paper presents an efficient and precise imaging algorithm for the large bandwidth sliding spotlight synthetic aperture radar (SAR). The existing sub-aperture processing method based on the baseband azimuth scaling (BAS) algorithm cannot cope with the high order phase coupling along the range and azimuth dimensions. This coupling problem causes defocusing along the range and azimuth dimensions. This paper proposes a generalized chirp scaling (GCS)-BAS processing algorithm, which is based on the GCS algorithm. It successfully mitigates the deep focus along the range dimension of a sub-aperture of the large bandwidth sliding spotlight SAR, as well as high order phase coupling along the range and azimuth dimensions. Additionally, the azimuth focusing can be achieved by this azimuth scaling method. Simulation results demonstrate the ability of the GCS-BAS algorithm to process the large bandwidth sliding spotlight SAR data. It is proven that great improvements of the focus depth and imaging accuracy are obtained via the GCS-BAS algorithm. PMID:28555057

Support Vector Machines Trained with Evolutionary Algorithms Employing Kernel Adatron for Large Scale Classification of Protein Structures.

PubMed

Arana-Daniel, Nancy; Gallegos, Alberto A; López-Franco, Carlos; Alanís, Alma Y; Morales, Jacob; López-Franco, Adriana

2016-01-01

With the increasing power of computers, the amount of data that can be processed in small periods of time has grown exponentially, as has the importance of classifying large-scale data efficiently. Support vector machines have shown good results classifying large amounts of high-dimensional data, such as data generated by protein structure prediction, spam recognition, medical diagnosis, optical character recognition and text classification, etc. Most state of the art approaches for large-scale learning use traditional optimization methods, such as quadratic programming or gradient descent, which makes the use of evolutionary algorithms for training support vector machines an area to be explored. The present paper proposes an approach that is simple to implement based on evolutionary algorithms and Kernel-Adatron for solving large-scale classification problems, focusing on protein structure prediction. The functional properties of proteins depend upon their three-dimensional structures. Knowing the structures of proteins is crucial for biology and can lead to improvements in areas such as medicine, agriculture and biofuels.

Energy efficiency and allometry of movement of swimming and flying animals.

PubMed

Bale, Rahul; Hao, Max; Bhalla, Amneet Pal Singh; Patankar, Neelesh A

2014-05-27

Which animals use their energy better during movement? One metric to answer this question is the energy cost per unit distance per unit weight. Prior data show that this metric decreases with mass, which is considered to imply that massive animals are more efficient. Although useful, this metric also implies that two dynamically equivalent animals of different sizes will not be considered equally efficient. We resolve this longstanding issue by first determining the scaling of energy cost per unit distance traveled. The scale is found to be M(2/3) or M(1/2), where M is the animal mass. Second, we introduce an energy-consumption coefficient (CE) defined as energy per unit distance traveled divided by this scale. CE is a measure of efficiency of swimming and flying, analogous to how drag coefficient quantifies aerodynamic drag on vehicles. Derivation of the energy-cost scale reveals that the assumption that undulatory swimmers spend energy to overcome drag in the direction of swimming is inappropriate. We derive allometric scalings that capture trends in data of swimming and flying animals over 10-20 orders of magnitude by mass. The energy-consumption coefficient reveals that swimmers beyond a critical mass, and most fliers are almost equally efficient as if they are dynamically equivalent; increasingly massive animals are not more efficient according to the proposed metric. Distinct allometric scalings are discovered for large and small swimmers. Flying animals are found to require relatively more energy compared with swimmers.

Energy efficiency and allometry of movement of swimming and flying animals

PubMed Central

Bale, Rahul; Hao, Max; Bhalla, Amneet Pal Singh; Patankar, Neelesh A.

2014-01-01

Which animals use their energy better during movement? One metric to answer this question is the energy cost per unit distance per unit weight. Prior data show that this metric decreases with mass, which is considered to imply that massive animals are more efficient. Although useful, this metric also implies that two dynamically equivalent animals of different sizes will not be considered equally efficient. We resolve this longstanding issue by first determining the scaling of energy cost per unit distance traveled. The scale is found to be M2/3 or M1/2, where M is the animal mass. Second, we introduce an energy-consumption coefficient (CE) defined as energy per unit distance traveled divided by this scale. CE is a measure of efficiency of swimming and flying, analogous to how drag coefficient quantifies aerodynamic drag on vehicles. Derivation of the energy-cost scale reveals that the assumption that undulatory swimmers spend energy to overcome drag in the direction of swimming is inappropriate. We derive allometric scalings that capture trends in data of swimming and flying animals over 10–20 orders of magnitude by mass. The energy-consumption coefficient reveals that swimmers beyond a critical mass, and most fliers are almost equally efficient as if they are dynamically equivalent; increasingly massive animals are not more efficient according to the proposed metric. Distinct allometric scalings are discovered for large and small swimmers. Flying animals are found to require relatively more energy compared with swimmers. PMID:24821764

Resource allocation for epidemic control in metapopulations.

PubMed

Ndeffo Mbah, Martial L; Gilligan, Christopher A

2011-01-01

Deployment of limited resources is an issue of major importance for decision-making in crisis events. This is especially true for large-scale outbreaks of infectious diseases. Little is known when it comes to identifying the most efficient way of deploying scarce resources for control when disease outbreaks occur in different but interconnected regions. The policy maker is frequently faced with the challenge of optimizing efficiency (e.g. minimizing the burden of infection) while accounting for social equity (e.g. equal opportunity for infected individuals to access treatment). For a large range of diseases described by a simple SIRS model, we consider strategies that should be used to minimize the discounted number of infected individuals during the course of an epidemic. We show that when faced with the dilemma of choosing between socially equitable and purely efficient strategies, the choice of the control strategy should be informed by key measurable epidemiological factors such as the basic reproductive number and the efficiency of the treatment measure. Our model provides new insights for policy makers in the optimal deployment of limited resources for control in the event of epidemic outbreaks at the landscape scale.

[Effect of pilot UASB-SFSBR-MAP process for the large scale swine wastewater treatment].

PubMed

Wang, Liang; Chen, Chong-Jun; Chen, Ying-Xu; Wu, Wei-Xiang

2013-03-01

In this paper, a treatment process consisted of UASB, step-fed sequencing batch reactor (SFSBR) and magnesium ammonium phosphate precipitation reactor (MAP) was built to treat the large scale swine wastewater, which aimed at overcoming drawbacks of conventional anaerobic-aerobic treatment process and SBR treatment process, such as the low denitrification efficiency, high operating costs and high nutrient losses and so on. Based on the treatment process, a pilot engineering was constructed. It was concluded from the experiment results that the removal efficiency of COD, NH4(+) -N and TP reached 95.1%, 92.7% and 88.8%, the recovery rate of NH4(+) -N and TP by MAP process reached 23.9% and 83.8%, the effluent quality was superior to the discharge standard of pollutants for livestock and poultry breeding (GB 18596-2001), mass concentration of COD, TN, NH4(+) -N, TP and SS were not higher than 135, 116, 43, 7.3 and 50 mg x L(-1) respectively. The process developed was reliable, kept self-balance of carbon source and alkalinity, reached high nutrient recovery efficiency. And the operating cost was equal to that of the traditional anaerobic-aerobic treatment process. So the treatment process could provide a high value of application and dissemination and be fit for the treatment pf the large scale swine wastewater in China.

Measuring the efficiency of dental departments in medical centers: a nonparametric analysis approach.

PubMed

Wang, Su-Chen; Tsai, Chi-Cheng; Huang, Shun-Te; Hong, Yu-Jue

2002-12-01

Data envelopment analysis (DEA), a cross-sectional study design based on secondary data analysis, was used to evaluate the relative operational efficiency of 16 dental departments in medical centers in Taiwan in 1999. The results indicated that 68.7% of all dental departments in medical centers had poor performance in terms of overall efficiency and scale efficiency. All relatively efficient dental departments were in private medical centers. Half of these dental departments were unable to fully utilize available medical resources. 75.0% of public medical centers did not take full advantage of medical resources at their disposal. In the returns to scale, 56.3% of dental departments in medical centers exhibited increasing returns to scale, due to the insufficient scale influencing overall hospital operational efficiency. Public medical centers accounted for 77.8% of the institutions affected. The scale of dental departments in private medical centers was more appropriate than those in public medical centers. In the sensitivity analysis, the numbers of residents, interns, and published papers were used to assess teaching and research. Greater emphasis on teaching and research in medical centers has a large effect on the relative inefficiency of hospital operation. Dental departments in private medical centers had a higher mean overall efficiency score than those in public medical centers, and the overall efficiency of dental departments in non-university hospitals was greater than those in university hospitals. There was no information to evaluate the long-term efficiency of each dental department in all hospitals. A different combination of input and output variables, using common multipliers for efficiency value measurements in DEA, may help establish different pioneering dental departments in hospitals.

Real Time Text Analysis

NASA Astrophysics Data System (ADS)

Senthilkumar, K.; Ruchika Mehra Vijayan, E.

2017-11-01

This paper aims to illustrate real time analysis of large scale data. For practical implementation we are performing sentiment analysis on live Twitter feeds for each individual tweet. To analyze sentiments we will train our data model on sentiWordNet, a polarity assigned wordNet sample by Princeton University. Our main objective will be to efficiency analyze large scale data on the fly using distributed computation. Apache Spark and Apache Hadoop eco system is used as distributed computation platform with Java as development language

Project Management Life Cycle Models to Improve Management in High-rise Construction

NASA Astrophysics Data System (ADS)

Burmistrov, Andrey; Siniavina, Maria; Iliashenko, Oksana

2018-03-01

The paper describes a possibility to improve project management in high-rise buildings construction through the use of various Project Management Life Cycle Models (PMLC models) based on traditional and agile project management approaches. Moreover, the paper describes, how the split the whole large-scale project to the "project chain" will create the factor for better manageability of the large-scale buildings project and increase the efficiency of the activities of all participants in such projects.

Commentary: Environmental nanophotonics and energy

NASA Astrophysics Data System (ADS)

Smith, Geoff B.

2011-01-01

The reasons nanophotonics is proving central to meeting the need for large gains in energy efficiency and renewable energy supply are analyzed. It enables optimum management and use of environmental energy flows at low cost and on a sufficient scale by providing spectral, directional and temporal control in tune with radiant flows from the sun, and the local atmosphere. Benefits and problems involved in large scale manufacture and deployment are discussed including how managing and avoiding safety issues in some nanosystems will occur, a process long established in nature.

BSIFT: toward data-independent codebook for large scale image search.

PubMed

Zhou, Wengang; Li, Houqiang; Hong, Richang; Lu, Yijuan; Tian, Qi

2015-03-01

Bag-of-Words (BoWs) model based on Scale Invariant Feature Transform (SIFT) has been widely used in large-scale image retrieval applications. Feature quantization by vector quantization plays a crucial role in BoW model, which generates visual words from the high- dimensional SIFT features, so as to adapt to the inverted file structure for the scalable retrieval. Traditional feature quantization approaches suffer several issues, such as necessity of visual codebook training, limited reliability, and update inefficiency. To avoid the above problems, in this paper, a novel feature quantization scheme is proposed to efficiently quantize each SIFT descriptor to a descriptive and discriminative bit-vector, which is called binary SIFT (BSIFT). Our quantizer is independent of image collections. In addition, by taking the first 32 bits out from BSIFT as code word, the generated BSIFT naturally lends itself to adapt to the classic inverted file structure for image indexing. Moreover, the quantization error is reduced by feature filtering, code word expansion, and query sensitive mask shielding. Without any explicit codebook for quantization, our approach can be readily applied in image search in some resource-limited scenarios. We evaluate the proposed algorithm for large scale image search on two public image data sets. Experimental results demonstrate the index efficiency and retrieval accuracy of our approach.

Large-scale production of lipoplexes with long shelf-life.

PubMed

Clement, Jule; Kiefer, Karin; Kimpfler, Andrea; Garidel, Patrick; Peschka-Süss, Regine

2005-01-01

The instability of lipoplex formulations is a major obstacle to overcome before their commercial application in gene therapy. In this study, a continuous mixing technique for the large-scale preparation of lipoplexes followed by lyophilisation for increased stability and shelf-life has been developed. Lipoplexes were analysed for transfection efficiency and cytotoxicity in human aorta smooth muscle cells (HASMC) and a rat smooth muscle cell line (A-10 SMC). Homogeneity of lipid/DNA-products was investigated by photon correlation spectroscopy (PCS) and cryotransmission electron microscopy (cryo-TEM). Studies have been undertaken with DAC-30, a composition of 3beta-[N-(N,N'-dimethylaminoethane)-carbamoyl]-cholesterol (DAC-Chol) and dioleylphosphatidylethanolamine (DOPE) and a green fluorescent protein (GFP) expressing marker plasmid. A continuous mixing technique was compared to the small-scale preparation of lipoplexes by pipetting. Individual steps of the continuous mixing process were evaluated in order to optimise the manufacturing technique: lipid/plasmid ratio, composition of transfection medium, pre-treatment of the lipid, size of the mixing device, mixing procedure and the influence of the lyophilisation process. It could be shown that the method developed for production of lipoplexes on a large scale under sterile conditions led to lipoplexes with good transfection efficiencies combined with low cytotoxicity, improved characteristics and long shelf-life.

A study of the efficiency of hydrogen liquefaction. [jet aircraft applications

NASA Technical Reports Server (NTRS)

Baker, C. R.; Shaner, R. L.

1976-01-01

The search for an environmentally acceptable fuel to eventually replace petroleum-based fuels for long-range jet aircraft has singled out liquid hydrogen as an outstanding candidate. Hydrogen liquefaction is discussed, along with the effect of several operating parameters on process efficiency. A feasible large-scale commercial hydrogen liquefaction facility based on the results of the efficiency study is described. Potential future improvements in hydrogen liquefaction are noted.

A novel representation of groundwater dynamics in large-scale land surface modelling

NASA Astrophysics Data System (ADS)

Rahman, Mostaquimur; Rosolem, Rafael; Kollet, Stefan

2017-04-01

Land surface processes are connected to groundwater dynamics via shallow soil moisture. For example, groundwater affects evapotranspiration (by influencing the variability of soil moisture) and runoff generation mechanisms. However, contemporary Land Surface Models (LSM) generally consider isolated soil columns and free drainage lower boundary condition for simulating hydrology. This is mainly due to the fact that incorporating detailed groundwater dynamics in LSMs usually requires considerable computing resources, especially for large-scale applications (e.g., continental to global). Yet, these simplifications undermine the potential effect of groundwater dynamics on land surface mass and energy fluxes. In this study, we present a novel approach of representing high-resolution groundwater dynamics in LSMs that is computationally efficient for large-scale applications. This new parameterization is incorporated in the Joint UK Land Environment Simulator (JULES) and tested at the continental-scale.

The effects of magnetic fields and protostellar feedback on low-mass cluster formation

NASA Astrophysics Data System (ADS)

Cunningham, Andrew J.; Krumholz, Mark R.; McKee, Christopher F.; Klein, Richard I.

2018-05-01

We present a large suite of simulations of the formation of low-mass star clusters. Our simulations include an extensive set of physical processes - magnetohydrodynamics, radiative transfer, and protostellar outflows - and span a wide range of virial parameters and magnetic field strengths. Comparing the outcomes of our simulations to observations, we find that simulations remaining close to virial balance throughout their history produce star formation efficiencies and initial mass function (IMF) peaks that are stable in time and in reasonable agreement with observations. Our results indicate that small-scale dissipation effects near the protostellar surface provide a feedback loop for stabilizing the star formation efficiency. This is true regardless of whether the balance is maintained by input of energy from large-scale forcing or by strong magnetic fields that inhibit collapse. In contrast, simulations that leave virial balance and undergo runaway collapse form stars too efficiently and produce an IMF that becomes increasingly top heavy with time. In all cases, we find that the competition between magnetic flux advection towards the protostar and outward advection due to magnetic interchange instabilities, and the competition between turbulent amplification and reconnection close to newly formed protostars renders the local magnetic field structure insensitive to the strength of the large-scale field, ensuring that radiation is always more important than magnetic support in setting the fragmentation scale and thus the IMF peak mass. The statistics of multiple stellar systems are similarly insensitive to variations in the initial conditions and generally agree with observations within the range of statistical uncertainty.

Accurate and Efficient Parallel Implementation of an Effective Linear-Scaling Direct Random Phase Approximation Method.

PubMed

Graf, Daniel; Beuerle, Matthias; Schurkus, Henry F; Luenser, Arne; Savasci, Gökcen; Ochsenfeld, Christian

2018-05-08

An efficient algorithm for calculating the random phase approximation (RPA) correlation energy is presented that is as accurate as the canonical molecular orbital resolution-of-the-identity RPA (RI-RPA) with the important advantage of an effective linear-scaling behavior (instead of quartic) for large systems due to a formulation in the local atomic orbital space. The high accuracy is achieved by utilizing optimized minimax integration schemes and the local Coulomb metric attenuated by the complementary error function for the RI approximation. The memory bottleneck of former atomic orbital (AO)-RI-RPA implementations ( Schurkus, H. F.; Ochsenfeld, C. J. Chem. Phys. 2016 , 144 , 031101 and Luenser, A.; Schurkus, H. F.; Ochsenfeld, C. J. Chem. Theory Comput. 2017 , 13 , 1647 - 1655 ) is addressed by precontraction of the large 3-center integral matrix with the Cholesky factors of the ground state density reducing the memory requirements of that matrix by a factor of [Formula: see text]. Furthermore, we present a parallel implementation of our method, which not only leads to faster RPA correlation energy calculations but also to a scalable decrease in memory requirements, opening the door for investigations of large molecules even on small- to medium-sized computing clusters. Although it is known that AO methods are highly efficient for extended systems, where sparsity allows for reaching the linear-scaling regime, we show that our work also extends the applicability when considering highly delocalized systems for which no linear scaling can be achieved. As an example, the interlayer distance of two covalent organic framework pore fragments (comprising 384 atoms in total) is analyzed.

Precipitation Efficiency in the Tropical Deep Convective Regime

NASA Technical Reports Server (NTRS)

Li, Xiaofan; Sui, C.-H.; Lau, K.-M.; Lau, William K. M. (Technical Monitor)

2001-01-01

Precipitation efficiency in the tropical deep convective regime is analyzed based on a 2-D cloud resolving simulation. The cloud resolving model is forced by the large-scale vertical velocity and zonal wind and large-scale horizontal advections derived from TOGA COARE for a 20-day period. Precipitation efficiency may be defined as a ratio of surface rain rate to sum of surface evaporation and moisture convergence (LSPE) or a ratio of surface rain rate to sum of condensation and deposition rates of supersaturated vapor (CMPE). Moisture budget shows that the atmosphere is moistened (dryed) when the LSPE is less (more) than 100 %. The LSPE could be larger than 100 % for strong convection. This indicates that the drying processes should be included in cumulus parameterization to avoid moisture bias. Statistical analysis shows that the sum of the condensation and deposition rates is bout 80 % of the sum of the surface evaporation rate and moisture convergence, which ads to proportional relation between the two efficiencies when both efficiencies are less han 100 %. The CMPE increases with increasing mass-weighted mean temperature and creasing surface rain rate. This suggests that precipitation is more efficient for warm environment and strong convection. Approximate balance of rates among the condensation, deposition, rain, and the raindrop evaporation is used to derive an analytical solution of the CMPE.

3-D imaging of large scale buried structure by 1-D inversion of very early time electromagnetic (VETEM) data

USGS Publications Warehouse

Aydmer, A.A.; Chew, W.C.; Cui, T.J.; Wright, D.L.; Smith, D.V.; Abraham, J.D.

2001-01-01

A simple and efficient method for large scale three-dimensional (3-D) subsurface imaging of inhomogeneous background is presented. One-dimensional (1-D) multifrequency distorted Born iterative method (DBIM) is employed in the inversion. Simulation results utilizing synthetic scattering data are given. Calibration of the very early time electromagnetic (VETEM) experimental waveforms is detailed along with major problems encountered in practice and their solutions. This discussion is followed by the results of a large scale application of the method to the experimental data provided by the VETEM system of the U.S. Geological Survey. The method is shown to have a computational complexity that is promising for on-site inversion.

Interface-Resolving Simulation of Collision Efficiency of Cloud Droplets

NASA Astrophysics Data System (ADS)

Wang, Lian-Ping; Peng, Cheng; Rosa, Bodgan; Onishi, Ryo

2017-11-01

Small-scale air turbulence could enhance the geometric collision rate of cloud droplets while large-scale air turbulence could augment the diffusional growth of cloud droplets. Air turbulence could also enhance the collision efficiency of cloud droplets. Accurate simulation of collision efficiency, however, requires capture of the multi-scale droplet-turbulence and droplet-droplet interactions, which has only been partially achieved in the recent past using the hybrid direct numerical simulation (HDNS) approach. % where Stokes disturbance flow is assumed. The HDNS approach has two major drawbacks: (1) the short-range droplet-droplet interaction is not treated rigorously; (2) the finite-Reynolds number correction to the collision efficiency is not included. In this talk, using two independent numerical methods, we will develop an interface-resolved simulation approach in which the disturbance flows are directly resolved numerically, combined with a rigorous lubrication correction model for near-field droplet-droplet interaction. This multi-scale approach is first used to study the effect of finite flow Reynolds numbers on the droplet collision efficiency in still air. Our simulation results show a significant finite-Re effect on collision efficiency when the droplets are of similar sizes. Preliminary results on integrating this approach in a turbulent flow laden with droplets will also be presented. This work is partially supported by the National Science Foundation.

A small-scale, rolled-membrane microfluidic artificial lung designed towards future large area manufacturing.

PubMed

Thompson, A J; Marks, L H; Goudie, M J; Rojas-Pena, A; Handa, H; Potkay, J A

2017-03-01

Artificial lungs have been used in the clinic for multiple decades to supplement patient pulmonary function. Recently, small-scale microfluidic artificial lungs (μAL) have been demonstrated with large surface area to blood volume ratios, biomimetic blood flow paths, and pressure drops compatible with pumpless operation. Initial small-scale microfluidic devices with blood flow rates in the μ l/min to ml/min range have exhibited excellent gas transfer efficiencies; however, current manufacturing techniques may not be suitable for scaling up to human applications. Here, we present a new manufacturing technology for a microfluidic artificial lung in which the structure is assembled via a continuous "rolling" and bonding procedure from a single, patterned layer of polydimethyl siloxane (PDMS). This method is demonstrated in a small-scale four-layer device, but is expected to easily scale to larger area devices. The presented devices have a biomimetic branching blood flow network, 10  μ m tall artificial capillaries, and a 66  μ m thick gas transfer membrane. Gas transfer efficiency in blood was evaluated over a range of blood flow rates (0.1-1.25 ml/min) for two different sweep gases (pure O 2 , atmospheric air). The achieved gas transfer data closely follow predicted theoretical values for oxygenation and CO 2 removal, while pressure drop is marginally higher than predicted. This work is the first step in developing a scalable method for creating large area microfluidic artificial lungs. Although designed for microfluidic artificial lungs, the presented technique is expected to result in the first manufacturing method capable of simply and easily creating large area microfluidic devices from PDMS.

High-efficiency nanostructured silicon solar cells on a large scale realized through the suppression of recombination channels.

PubMed

Zhong, Sihua; Huang, Zengguang; Lin, Xingxing; Zeng, Yang; Ma, Yechi; Shen, Wenzhong

2015-01-21

Nanostructured silicon solar cells show great potential for new-generation photovoltaics due to their ability to approach ideal light-trapping. However, the nanofeatured morphology that brings about the optical benefits also introduces new recombination channels, and severe deterioration in the electrical performance even outweighs the gain in optics in most attempts. This Research News article aims to review the recent progress in the suppression of carrier recombination in silicon nanostructures, with the emphasis on the optimization of surface morphology and controllable nanostructure height and emitter doping concentration, as well as application of dielectric passivation coatings, providing design rules to realize high-efficiency nanostructured silicon solar cells on a large scale. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Strategy for large-scale isolation of enantiomers in drug discovery.

PubMed

Leek, Hanna; Thunberg, Linda; Jonson, Anna C; Öhlén, Kristina; Klarqvist, Magnus

2017-01-01

A strategy for large-scale chiral resolution is illustrated by the isolation of pure enantiomer from a 5kg batch. Results from supercritical fluid chromatography will be presented and compared with normal phase liquid chromatography. Solubility of the compound in the supercritical mobile phase was shown to be the limiting factor. To circumvent this, extraction injection was used but shown not to be efficient for this compound. Finally, a method for chiral resolution by crystallization was developed and applied to give diastereomeric salt with an enantiomeric excess of 99% at a 91% yield. Direct access to a diverse separation tool box will be shown to be essential for solving separation problems in the most cost and time efficient way. Copyright © 2016 Elsevier Ltd. All rights reserved.

The scale-dependent market trend: Empirical evidences using the lagged DFA method

NASA Astrophysics Data System (ADS)

Li, Daye; Kou, Zhun; Sun, Qiankun

2015-09-01

In this paper we make an empirical research and test the efficiency of 44 important market indexes in multiple scales. A modified method based on the lagged detrended fluctuation analysis is utilized to maximize the information of long-term correlations from the non-zero lags and keep the margin of errors small when measuring the local Hurst exponent. Our empirical result illustrates that a common pattern can be found in the majority of the measured market indexes which tend to be persistent (with the local Hurst exponent > 0.5) in the small time scale, whereas it displays significant anti-persistent characteristics in large time scales. Moreover, not only the stock markets but also the foreign exchange markets share this pattern. Considering that the exchange markets are only weakly synchronized with the economic cycles, it can be concluded that the economic cycles can cause anti-persistence in the large time scale but there are also other factors at work. The empirical result supports the view that financial markets are multi-fractal and it indicates that deviations from efficiency and the type of model to describe the trend of market price are dependent on the forecasting horizon.

Dynamic effective connectivity in cortically embedded systems of recurrently coupled synfire chains.

PubMed

Trengove, Chris; Diesmann, Markus; van Leeuwen, Cees

2016-02-01

As a candidate mechanism of neural representation, large numbers of synfire chains can efficiently be embedded in a balanced recurrent cortical network model. Here we study a model in which multiple synfire chains of variable strength are randomly coupled together to form a recurrent system. The system can be implemented both as a large-scale network of integrate-and-fire neurons and as a reduced model. The latter has binary-state pools as basic units but is otherwise isomorphic to the large-scale model, and provides an efficient tool for studying its behavior. Both the large-scale system and its reduced counterpart are able to sustain ongoing endogenous activity in the form of synfire waves, the proliferation of which is regulated by negative feedback caused by collateral noise. Within this equilibrium, diverse repertoires of ongoing activity are observed, including meta-stability and multiple steady states. These states arise in concert with an effective connectivity structure (ECS). The ECS admits a family of effective connectivity graphs (ECGs), parametrized by the mean global activity level. Of these graphs, the strongly connected components and their associated out-components account to a large extent for the observed steady states of the system. These results imply a notion of dynamic effective connectivity as governing neural computation with synfire chains, and related forms of cortical circuitry with complex topologies.

Large Scale Frequent Pattern Mining using MPI One-Sided Model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Vishnu, Abhinav; Agarwal, Khushbu

In this paper, we propose a work-stealing runtime --- Library for Work Stealing LibWS --- using MPI one-sided model for designing scalable FP-Growth --- {\\em de facto} frequent pattern mining algorithm --- on large scale systems. LibWS provides locality efficient and highly scalable work-stealing techniques for load balancing on a variety of data distributions. We also propose a novel communication algorithm for FP-growth data exchange phase, which reduces the communication complexity from state-of-the-art O(p) to O(f + p/f) for p processes and f frequent attributed-ids. FP-Growth is implemented using LibWS and evaluated on several work distributions and support counts. Anmore » experimental evaluation of the FP-Growth on LibWS using 4096 processes on an InfiniBand Cluster demonstrates excellent efficiency for several work distributions (87\\% efficiency for Power-law and 91% for Poisson). The proposed distributed FP-Tree merging algorithm provides 38x communication speedup on 4096 cores.« less

New Insights on Hydro-Climate Feedback Processes over the Tropical Ocean from TRMM

NASA Technical Reports Server (NTRS)

Lau, William K. M.; Wu, H. T.; Li, Xiaofan; Sui, C. H.

2002-01-01

In this paper, we study hydro-climate feedback processes over the tropical oceans, by examining the relationships among large scale circulation and Tropical Rainfall Measuring Mission Microwave Imager-Sea Surface Temperature (TMI-SST), and a range of TRMM rain products including rain rate, cloud liquid water, precipitable water, cloud types and areal coverage, and precipitation efficiency. Results show that for a warm event (1998), the 28C threshold of convective precipitation is quite well defined over the tropical oceans. However, for a cold event (1999), the SST threshold is less well defined, especially over the central and eastern Pacific cold tongue, where stratiform rain occurs at much lower than 28 C. Precipitation rates and cloud liquid water are found to be more closely related to the large scale vertical motion than to the underlying SST. While total columnar water vapor is more strongly dependent on SST. For a large domain, over the eastern Pacific, we find that the areal extent of the cloudy region tends to shrink as the SST increases. Examination of the relationship between cloud liquid water and rain rate suggests that the residence time of cloud liquid water tends to be shorter, associated with higher precipitation efficiency in a warmer climate. It is hypothesized that the reduction in cloudy area may be influenced both by the shift in large scale cloud patterns in response to changes in large scale forcings, and possible increase in the cloud liquid water conversion to rain water in a warmer environment. Results of numerical experiments with the Goddard cloud resolving model to test the hypothesis will be discussed.

Efficient Storage Scheme of Covariance Matrix during Inverse Modeling

NASA Astrophysics Data System (ADS)

Mao, D.; Yeh, T. J.

2013-12-01

During stochastic inverse modeling, the covariance matrix of geostatistical based methods carries the information about the geologic structure. Its update during iterations reflects the decrease of uncertainty with the incorporation of observed data. For large scale problem, its storage and update cost too much memory and computational resources. In this study, we propose a new efficient storage scheme for storage and update. Compressed Sparse Column (CSC) format is utilized to storage the covariance matrix, and users can assign how many data they prefer to store based on correlation scales since the data beyond several correlation scales are usually not very informative for inverse modeling. After every iteration, only the diagonal terms of the covariance matrix are updated. The off diagonal terms are calculated and updated based on shortened correlation scales with a pre-assigned exponential model. The correlation scales are shortened by a coefficient, i.e. 0.95, every iteration to show the decrease of uncertainty. There is no universal coefficient for all the problems and users are encouraged to try several times. This new scheme is tested with 1D examples first. The estimated results and uncertainty are compared with the traditional full storage method. In the end, a large scale numerical model is utilized to validate this new scheme.

Demonstration of Hadoop-GIS: A Spatial Data Warehousing System Over MapReduce.

PubMed

Aji, Ablimit; Sun, Xiling; Vo, Hoang; Liu, Qioaling; Lee, Rubao; Zhang, Xiaodong; Saltz, Joel; Wang, Fusheng

2013-11-01

The proliferation of GPS-enabled devices, and the rapid improvement of scientific instruments have resulted in massive amounts of spatial data in the last decade. Support of high performance spatial queries on large volumes data has become increasingly important in numerous fields, which requires a scalable and efficient spatial data warehousing solution as existing approaches exhibit scalability limitations and efficiency bottlenecks for large scale spatial applications. In this demonstration, we present Hadoop-GIS - a scalable and high performance spatial query system over MapReduce. Hadoop-GIS provides an efficient spatial query engine to process spatial queries, data and space based partitioning, and query pipelines that parallelize queries implicitly on MapReduce. Hadoop-GIS also provides an expressive, SQL-like spatial query language for workload specification. We will demonstrate how spatial queries are expressed in spatially extended SQL queries, and submitted through a command line/web interface for execution. Parallel to our system demonstration, we explain the system architecture and details on how queries are translated to MapReduce operators, optimized, and executed on Hadoop. In addition, we will showcase how the system can be used to support two representative real world use cases: large scale pathology analytical imaging, and geo-spatial data warehousing.

An efficient and reliable predictive method for fluidized bed simulation

DOE PAGES

Lu, Liqiang; Benyahia, Sofiane; Li, Tingwen

2017-06-13

In past decades, the continuum approach was the only practical technique to simulate large-scale fluidized bed reactors because discrete approaches suffer from the cost of tracking huge numbers of particles and their collisions. This study significantly improved the computation speed of discrete particle methods in two steps: First, the time-driven hard-sphere (TDHS) algorithm with a larger time-step is proposed allowing a speedup of 20-60 times; second, the number of tracked particles is reduced by adopting the coarse-graining technique gaining an additional 2-3 orders of magnitude speedup of the simulations. A new velocity correction term was introduced and validated in TDHSmore » to solve the over-packing issue in dense granular flow. The TDHS was then coupled with the coarse-graining technique to simulate a pilot-scale riser. The simulation results compared well with experiment data and proved that this new approach can be used for efficient and reliable simulations of large-scale fluidized bed systems.« less

An efficient and reliable predictive method for fluidized bed simulation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lu, Liqiang; Benyahia, Sofiane; Li, Tingwen

2017-06-29

In past decades, the continuum approach was the only practical technique to simulate large-scale fluidized bed reactors because discrete approaches suffer from the cost of tracking huge numbers of particles and their collisions. This study significantly improved the computation speed of discrete particle methods in two steps: First, the time-driven hard-sphere (TDHS) algorithm with a larger time-step is proposed allowing a speedup of 20-60 times; second, the number of tracked particles is reduced by adopting the coarse-graining technique gaining an additional 2-3 orders of magnitude speedup of the simulations. A new velocity correction term was introduced and validated in TDHSmore » to solve the over-packing issue in dense granular flow. The TDHS was then coupled with the coarse-graining technique to simulate a pilot-scale riser. The simulation results compared well with experiment data and proved that this new approach can be used for efficient and reliable simulations of large-scale fluidized bed systems.« less

Non-linear characteristics and long-range correlations in Asian stock markets

NASA Astrophysics Data System (ADS)

Jiang, J.; Ma, K.; Cai, X.

2007-05-01

We test several non-linear characteristics of Asian stock markets, which indicates the failure of efficient market hypothesis and shows the essence of fractal of the financial markets. In addition, by using the method of detrended fluctuation analysis (DFA) to investigate the long range correlation of the volatility in the stock markets, we find that the crossover phenomena exist in the results of DFA. Further, in the region of small volatility, the scaling behavior is more complicated; in the region of large volatility, the scaling exponent is close to 0.5, which suggests the market is more efficient. All these results may indicate the possibility of characteristic multifractal scaling behaviors of the financial markets.

STE thrust chamber technology: Main injector technology program and nozzle Advanced Development Program (ADP)

NASA Technical Reports Server (NTRS)

1993-01-01

The purpose of the STME Main Injector Program was to enhance the technology base for the large-scale main injector-combustor system of oxygen-hydrogen booster engines in the areas of combustion efficiency, chamber heating rates, and combustion stability. The initial task of the Main Injector Program, focused on analysis and theoretical predictions using existing models, was complemented by the design, fabrication, and test at MSFC of a subscale calorimetric, 40,000-pound thrust class, axisymmetric thrust chamber operating at approximately 2,250 psi and a 7:1 expansion ratio. Test results were used to further define combustion stability bounds, combustion efficiency, and heating rates using a large injector scale similar to the Pratt & Whitney (P&W) STME main injector design configuration including the tangential entry swirl coaxial injection elements. The subscale combustion data was used to verify and refine analytical modeling simulation and extend the database range to guide the design of the large-scale system main injector. The subscale injector design incorporated fuel and oxidizer flow area control features which could be varied; this allowed testing of several design points so that the STME conditions could be bracketed. The subscale injector design also incorporated high-reliability and low-cost fabrication techniques such as a one-piece electrical discharged machined (EDMed) interpropellant plate. Both subscale and large-scale injectors incorporated outer row injector elements with scarfed tip features to allow evaluation of reduced heating rates to the combustion chamber.

Development of optimal grinding and polishing tools for aspheric surfaces

NASA Astrophysics Data System (ADS)

Burge, James H.; Anderson, Bill; Benjamin, Scott; Cho, Myung K.; Smith, Koby Z.; Valente, Martin J.

2001-12-01

The ability to grind and polish steep aspheric surfaces to high quality is limited by the tools used for working the surface. The optician prefers to use large, stiff tools to get good natural smoothing, avoiding small scale surface errors. This is difficult for steep aspheres because the tools must have sufficient compliance to fit the aspheric surface, yet we wish the tools to be stiff so they wear down high regions on the surface. This paper presents a toolkit for designing optimal tools that provide large scale compliance to fit the aspheric surface, yet maintain small scale stiffness for efficient polishing.

The morphing of geographical features by Fourier transformation.

PubMed

Li, Jingzhong; Liu, Pengcheng; Yu, Wenhao; Cheng, Xiaoqiang

2018-01-01

This paper presents a morphing model of vector geographical data based on Fourier transformation. This model involves three main steps. They are conversion from vector data to Fourier series, generation of intermediate function by combination of the two Fourier series concerning a large scale and a small scale, and reverse conversion from combination function to vector data. By mirror processing, the model can also be used for morphing of linear features. Experimental results show that this method is sensitive to scale variations and it can be used for vector map features' continuous scale transformation. The efficiency of this model is linearly related to the point number of shape boundary and the interceptive value n of Fourier expansion. The effect of morphing by Fourier transformation is plausible and the efficiency of the algorithm is acceptable.

Communication: A reduced scaling J-engine based reformulation of SOS-MP2 using graphics processing units.

PubMed

Maurer, S A; Kussmann, J; Ochsenfeld, C

2014-08-07

We present a low-prefactor, cubically scaling scaled-opposite-spin second-order Møller-Plesset perturbation theory (SOS-MP2) method which is highly suitable for massively parallel architectures like graphics processing units (GPU). The scaling is reduced from O(N⁵) to O(N³) by a reformulation of the MP2-expression in the atomic orbital basis via Laplace transformation and the resolution-of-the-identity (RI) approximation of the integrals in combination with efficient sparse algebra for the 3-center integral transformation. In contrast to previous works that employ GPUs for post Hartree-Fock calculations, we do not simply employ GPU-based linear algebra libraries to accelerate the conventional algorithm. Instead, our reformulation allows to replace the rate-determining contraction step with a modified J-engine algorithm, that has been proven to be highly efficient on GPUs. Thus, our SOS-MP2 scheme enables us to treat large molecular systems in an accurate and efficient manner on a single GPU-server.

Using relational databases for improved sequence similarity searching and large-scale genomic analyses.

PubMed

Mackey, Aaron J; Pearson, William R

2004-10-01

Relational databases are designed to integrate diverse types of information and manage large sets of search results, greatly simplifying genome-scale analyses. Relational databases are essential for management and analysis of large-scale sequence analyses, and can also be used to improve the statistical significance of similarity searches by focusing on subsets of sequence libraries most likely to contain homologs. This unit describes using relational databases to improve the efficiency of sequence similarity searching and to demonstrate various large-scale genomic analyses of homology-related data. This unit describes the installation and use of a simple protein sequence database, seqdb_demo, which is used as a basis for the other protocols. These include basic use of the database to generate a novel sequence library subset, how to extend and use seqdb_demo for the storage of sequence similarity search results and making use of various kinds of stored search results to address aspects of comparative genomic analysis.

Completing the mechanical energy pathways in turbulent Rayleigh-Bénard convection.

PubMed

Gayen, Bishakhdatta; Hughes, Graham O; Griffiths, Ross W

2013-09-20

A new, more complete view of the mechanical energy budget for Rayleigh-Bénard convection is developed and examined using three-dimensional numerical simulations at large Rayleigh numbers and Prandtl number of 1. The driving role of available potential energy is highlighted. The relative magnitudes of different energy conversions or pathways change significantly over the range of Rayleigh numbers Ra ~ 10(7)-10(13). At Ra < 10(7) small-scale turbulent motions are energized directly from available potential energy via turbulent buoyancy flux and kinetic energy is dissipated at comparable rates by both the large- and small-scale motions. In contrast, at Ra ≥ 10(10) most of the available potential energy goes into kinetic energy of the large-scale flow, which undergoes shear instabilities that sustain small-scale turbulence. The irreversible mixing is largely confined to the unstable boundary layer, its rate exactly equal to the generation of available potential energy by the boundary fluxes, and mixing efficiency is 50%.

Mining the Mind Research Network: A Novel Framework for Exploring Large Scale, Heterogeneous Translational Neuroscience Research Data Sources

PubMed Central

Bockholt, Henry J.; Scully, Mark; Courtney, William; Rachakonda, Srinivas; Scott, Adam; Caprihan, Arvind; Fries, Jill; Kalyanam, Ravi; Segall, Judith M.; de la Garza, Raul; Lane, Susan; Calhoun, Vince D.

2009-01-01

A neuroinformatics (NI) system is critical to brain imaging research in order to shorten the time between study conception and results. Such a NI system is required to scale well when large numbers of subjects are studied. Further, when multiple sites participate in research projects organizational issues become increasingly difficult. Optimized NI applications mitigate these problems. Additionally, NI software enables coordination across multiple studies, leveraging advantages potentially leading to exponential research discoveries. The web-based, Mind Research Network (MRN), database system has been designed and improved through our experience with 200 research studies and 250 researchers from seven different institutions. The MRN tools permit the collection, management, reporting and efficient use of large scale, heterogeneous data sources, e.g., multiple institutions, multiple principal investigators, multiple research programs and studies, and multimodal acquisitions. We have collected and analyzed data sets on thousands of research participants and have set up a framework to automatically analyze the data, thereby making efficient, practical data mining of this vast resource possible. This paper presents a comprehensive framework for capturing and analyzing heterogeneous neuroscience research data sources that has been fully optimized for end-users to perform novel data mining. PMID:20461147

A Coarse-to-Fine Geometric Scale-Invariant Feature Transform for Large Size High Resolution Satellite Image Registration

PubMed Central

Chang, Xueli; Du, Siliang; Li, Yingying; Fang, Shenghui

2018-01-01

Large size high resolution (HR) satellite image matching is a challenging task due to local distortion, repetitive structures, intensity changes and low efficiency. In this paper, a novel matching approach is proposed for the large size HR satellite image registration, which is based on coarse-to-fine strategy and geometric scale-invariant feature transform (SIFT). In the coarse matching step, a robust matching method scale restrict (SR) SIFT is implemented at low resolution level. The matching results provide geometric constraints which are then used to guide block division and geometric SIFT in the fine matching step. The block matching method can overcome the memory problem. In geometric SIFT, with area constraints, it is beneficial for validating the candidate matches and decreasing searching complexity. To further improve the matching efficiency, the proposed matching method is parallelized using OpenMP. Finally, the sensing image is rectified to the coordinate of reference image via Triangulated Irregular Network (TIN) transformation. Experiments are designed to test the performance of the proposed matching method. The experimental results show that the proposed method can decrease the matching time and increase the number of matching points while maintaining high registration accuracy. PMID:29702589

Large-scale Exploration of Neuronal Morphologies Using Deep Learning and Augmented Reality.

PubMed

Li, Zhongyu; Butler, Erik; Li, Kang; Lu, Aidong; Ji, Shuiwang; Zhang, Shaoting

2018-02-12

Recently released large-scale neuron morphological data has greatly facilitated the research in neuroinformatics. However, the sheer volume and complexity of these data pose significant challenges for efficient and accurate neuron exploration. In this paper, we propose an effective retrieval framework to address these problems, based on frontier techniques of deep learning and binary coding. For the first time, we develop a deep learning based feature representation method for the neuron morphological data, where the 3D neurons are first projected into binary images and then learned features using an unsupervised deep neural network, i.e., stacked convolutional autoencoders (SCAEs). The deep features are subsequently fused with the hand-crafted features for more accurate representation. Considering the exhaustive search is usually very time-consuming in large-scale databases, we employ a novel binary coding method to compress feature vectors into short binary codes. Our framework is validated on a public data set including 58,000 neurons, showing promising retrieval precision and efficiency compared with state-of-the-art methods. In addition, we develop a novel neuron visualization program based on the techniques of augmented reality (AR), which can help users take a deep exploration of neuron morphologies in an interactive and immersive manner.

A first large-scale flood inundation forecasting model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Schumann, Guy J-P; Neal, Jeffrey C.; Voisin, Nathalie

2013-11-04

At present continental to global scale flood forecasting focusses on predicting at a point discharge, with little attention to the detail and accuracy of local scale inundation predictions. Yet, inundation is actually the variable of interest and all flood impacts are inherently local in nature. This paper proposes a first large scale flood inundation ensemble forecasting model that uses best available data and modeling approaches in data scarce areas and at continental scales. The model was built for the Lower Zambezi River in southeast Africa to demonstrate current flood inundation forecasting capabilities in large data-scarce regions. The inundation model domainmore » has a surface area of approximately 170k km2. ECMWF meteorological data were used to force the VIC (Variable Infiltration Capacity) macro-scale hydrological model which simulated and routed daily flows to the input boundary locations of the 2-D hydrodynamic model. Efficient hydrodynamic modeling over large areas still requires model grid resolutions that are typically larger than the width of many river channels that play a key a role in flood wave propagation. We therefore employed a novel sub-grid channel scheme to describe the river network in detail whilst at the same time representing the floodplain at an appropriate and efficient scale. The modeling system was first calibrated using water levels on the main channel from the ICESat (Ice, Cloud, and land Elevation Satellite) laser altimeter and then applied to predict the February 2007 Mozambique floods. Model evaluation showed that simulated flood edge cells were within a distance of about 1 km (one model resolution) compared to an observed flood edge of the event. Our study highlights that physically plausible parameter values and satisfactory performance can be achieved at spatial scales ranging from tens to several hundreds of thousands of km2 and at model grid resolutions up to several km2. However, initial model test runs in forecast mode revealed that it is crucial to account for basin-wide hydrological response time when assessing lead time performances notwithstanding structural limitations in the hydrological model and possibly large inaccuracies in precipitation data.« less

ResStock Analysis Tool | Buildings | NREL

Science.gov Websites

Energy and Cost Savings for U.S. Homes Contact Eric Wilson to learn how ResStock can benefit your approach to large-scale residential energy analysis by combining: Large public and private data sources uncovered $49 billion in potential annual utility bill savings through cost-effective energy efficiency

Exploiting multi-scale parallelism for large scale numerical modelling of laser wakefield accelerators

NASA Astrophysics Data System (ADS)

Fonseca, R. A.; Vieira, J.; Fiuza, F.; Davidson, A.; Tsung, F. S.; Mori, W. B.; Silva, L. O.

2013-12-01

A new generation of laser wakefield accelerators (LWFA), supported by the extreme accelerating fields generated in the interaction of PW-Class lasers and underdense targets, promises the production of high quality electron beams in short distances for multiple applications. Achieving this goal will rely heavily on numerical modelling to further understand the underlying physics and identify optimal regimes, but large scale modelling of these scenarios is computationally heavy and requires the efficient use of state-of-the-art petascale supercomputing systems. We discuss the main difficulties involved in running these simulations and the new developments implemented in the OSIRIS framework to address these issues, ranging from multi-dimensional dynamic load balancing and hybrid distributed/shared memory parallelism to the vectorization of the PIC algorithm. We present the results of the OASCR Joule Metric program on the issue of large scale modelling of LWFA, demonstrating speedups of over 1 order of magnitude on the same hardware. Finally, scalability to over ˜106 cores and sustained performance over ˜2 P Flops is demonstrated, opening the way for large scale modelling of LWFA scenarios.

Enabling large-scale viscoelastic calculations via neural network acceleration

NASA Astrophysics Data System (ADS)

Robinson DeVries, P.; Thompson, T. B.; Meade, B. J.

2017-12-01

One of the most significant challenges involved in efforts to understand the effects of repeated earthquake cycle activity are the computational costs of large-scale viscoelastic earthquake cycle models. Deep artificial neural networks (ANNs) can be used to discover new, compact, and accurate computational representations of viscoelastic physics. Once found, these efficient ANN representations may replace computationally intensive viscoelastic codes and accelerate large-scale viscoelastic calculations by more than 50,000%. This magnitude of acceleration enables the modeling of geometrically complex faults over thousands of earthquake cycles across wider ranges of model parameters and at larger spatial and temporal scales than have been previously possible. Perhaps most interestingly from a scientific perspective, ANN representations of viscoelastic physics may lead to basic advances in the understanding of the underlying model phenomenology. We demonstrate the potential of artificial neural networks to illuminate fundamental physical insights with specific examples.

Large-scale Advanced Prop-fan (LAP) technology assessment report

NASA Technical Reports Server (NTRS)

Degeorge, C. L.

1988-01-01

The technologically significant findings and accomplishments of the Large Scale Advanced Prop-Fan (LAP) program in the areas of aerodynamics, aeroelasticity, acoustics and materials and fabrication are described. The extent to which the program goals related to these disciplines were achieved is discussed, and recommendations for additional research are presented. The LAP program consisted of the design, manufacture and testing of a near full-scale Prop-Fan or advanced turboprop capable of operating efficiently at speeds to Mach .8. An aeroelastically scaled model of the LAP was also designed and fabricated. The goal of the program was to acquire data on Prop-Fan performance that would indicate the technology readiness of Prop-Fans for practical applications in commercial and military aviation.

An extended basis inexact shift-invert Lanczos for the efficient solution of large-scale generalized eigenproblems

NASA Astrophysics Data System (ADS)

Rewieński, M.; Lamecki, A.; Mrozowski, M.

2013-09-01

This paper proposes a technique, based on the Inexact Shift-Invert Lanczos (ISIL) method with Inexact Jacobi Orthogonal Component Correction (IJOCC) refinement, and a preconditioned conjugate-gradient (PCG) linear solver with multilevel preconditioner, for finding several eigenvalues for generalized symmetric eigenproblems. Several eigenvalues are found by constructing (with the ISIL process) an extended projection basis. Presented results of numerical experiments confirm the technique can be effectively applied to challenging, large-scale problems characterized by very dense spectra, such as resonant cavities with spatial dimensions which are large with respect to wavelengths of the resonating electromagnetic fields. It is also shown that the proposed scheme based on inexact linear solves delivers superior performance, as compared to methods which rely on exact linear solves, indicating tremendous potential of the 'inexact solve' concept. Finally, the scheme which generates an extended projection basis is found to provide a cost-efficient alternative to classical deflation schemes when several eigenvalues are computed.

Visual attention mitigates information loss in small- and large-scale neural codes

PubMed Central

Sprague, Thomas C; Saproo, Sameer; Serences, John T

2015-01-01

Summary The visual system transforms complex inputs into robust and parsimonious neural codes that efficiently guide behavior. Because neural communication is stochastic, the amount of encoded visual information necessarily decreases with each synapse. This constraint requires processing sensory signals in a manner that protects information about relevant stimuli from degradation. Such selective processing – or selective attention – is implemented via several mechanisms, including neural gain and changes in tuning properties. However, examining each of these effects in isolation obscures their joint impact on the fidelity of stimulus feature representations by large-scale population codes. Instead, large-scale activity patterns can be used to reconstruct representations of relevant and irrelevant stimuli, providing a holistic understanding about how neuron-level modulations collectively impact stimulus encoding. PMID:25769502

Characterizing Synergistic Water and Energy Efficiency at the Residential Scale Using a Cost Abatement Curve Approach

NASA Astrophysics Data System (ADS)

Stillwell, A. S.; Chini, C. M.; Schreiber, K. L.; Barker, Z. A.

2015-12-01

Energy and water are two increasingly correlated resources. Electricity generation at thermoelectric power plants requires cooling such that large water withdrawal and consumption rates are associated with electricity consumption. Drinking water and wastewater treatment require significant electricity inputs to clean, disinfect, and pump water. Due to this energy-water nexus, energy efficiency measures might be a cost-effective approach to reducing water use and water efficiency measures might support energy savings as well. This research characterizes the cost-effectiveness of different efficiency approaches in households by quantifying the direct and indirect water and energy savings that could be realized through efficiency measures, such as low-flow fixtures, energy and water efficient appliances, distributed generation, and solar water heating. Potential energy and water savings from these efficiency measures was analyzed in a product-lifetime adjusted economic model comparing efficiency measures to conventional counterparts. Results were displayed as cost abatement curves indicating the most economical measures to implement for a target reduction in water and/or energy consumption. These cost abatement curves are useful in supporting market innovation and investment in residential-scale efficiency.

Global efficiency of local immunization on complex networks

NASA Astrophysics Data System (ADS)

Hébert-Dufresne, Laurent; Allard, Antoine; Young, Jean-Gabriel; Dubé, Louis J.

2013-07-01

Epidemics occur in all shapes and forms: infections propagating in our sparse sexual networks, rumours and diseases spreading through our much denser social interactions, or viruses circulating on the Internet. With the advent of large databases and efficient analysis algorithms, these processes can be better predicted and controlled. In this study, we use different characteristics of network organization to identify the influential spreaders in 17 empirical networks of diverse nature using 2 epidemic models. We find that a judicious choice of local measures, based either on the network's connectivity at a microscopic scale or on its community structure at a mesoscopic scale, compares favorably to global measures, such as betweenness centrality, in terms of efficiency, practicality and robustness. We also develop an analytical framework that highlights a transition in the characteristic scale of different epidemic regimes. This allows to decide which local measure should govern immunization in a given scenario.

Global efficiency of local immunization on complex networks.

PubMed

Hébert-Dufresne, Laurent; Allard, Antoine; Young, Jean-Gabriel; Dubé, Louis J

2013-01-01

Epidemics occur in all shapes and forms: infections propagating in our sparse sexual networks, rumours and diseases spreading through our much denser social interactions, or viruses circulating on the Internet. With the advent of large databases and efficient analysis algorithms, these processes can be better predicted and controlled. In this study, we use different characteristics of network organization to identify the influential spreaders in 17 empirical networks of diverse nature using 2 epidemic models. We find that a judicious choice of local measures, based either on the network's connectivity at a microscopic scale or on its community structure at a mesoscopic scale, compares favorably to global measures, such as betweenness centrality, in terms of efficiency, practicality and robustness. We also develop an analytical framework that highlights a transition in the characteristic scale of different epidemic regimes. This allows to decide which local measure should govern immunization in a given scenario.

Dynamic ruptures on faults of complex geometry: insights from numerical simulations, from large-scale curvature to small-scale fractal roughness

NASA Astrophysics Data System (ADS)

Ulrich, T.; Gabriel, A. A.

2016-12-01

The geometry of faults is subject to a large degree of uncertainty. As buried structures being not directly observable, their complex shapes may only be inferred from surface traces, if available, or through geophysical methods, such as reflection seismology. As a consequence, most studies aiming at assessing the potential hazard of faults rely on idealized fault models, based on observable large-scale features. Yet, real faults are known to be wavy at all scales, their geometric features presenting similar statistical properties from the micro to the regional scale. The influence of roughness on the earthquake rupture process is currently a driving topic in the computational seismology community. From the numerical point of view, rough faults problems are challenging problems that require optimized codes able to run efficiently on high-performance computing infrastructure and simultaneously handle complex geometries. Physically, simulated ruptures hosted by rough faults appear to be much closer to source models inverted from observation in terms of complexity. Incorporating fault geometry on all scales may thus be crucial to model realistic earthquake source processes and to estimate more accurately seismic hazard. In this study, we use the software package SeisSol, based on an ADER-Discontinuous Galerkin scheme, to run our numerical simulations. SeisSol allows solving the spontaneous dynamic earthquake rupture problem and the wave propagation problem with high-order accuracy in space and time efficiently on large-scale machines. In this study, the influence of fault roughness on dynamic rupture style (e.g. onset of supershear transition, rupture front coherence, propagation of self-healing pulses, etc) at different length scales is investigated by analyzing ruptures on faults of varying roughness spectral content. In particular, we investigate the existence of a minimum roughness length scale in terms of rupture inherent length scales below which the rupture ceases to be sensible. Finally, the effect of fault geometry on ground-motions, in the near-field, is considered. Our simulations feature a classical linear slip weakening on the fault and a viscoplastic constitutive model off the fault. The benefits of using a more elaborate fast velocity-weakening friction law will also be considered.

Solar-Power System Produces High-Pressure Steam

NASA Technical Reports Server (NTRS)

Lansing, F. L.

1985-01-01

Combination of three multistaged solar collectors produces highpressure steam for large-scale continuously operating turbines for generating mechanical or electrical energy. Superheated water vapor drives turbines, attaining an overall system efficiency about 22 percent.

Analyzing big data with the hybrid interval regression methods.

PubMed

Huang, Chia-Hui; Yang, Keng-Chieh; Kao, Han-Ying

2014-01-01

Big data is a new trend at present, forcing the significant impacts on information technologies. In big data applications, one of the most concerned issues is dealing with large-scale data sets that often require computation resources provided by public cloud services. How to analyze big data efficiently becomes a big challenge. In this paper, we collaborate interval regression with the smooth support vector machine (SSVM) to analyze big data. Recently, the smooth support vector machine (SSVM) was proposed as an alternative of the standard SVM that has been proved more efficient than the traditional SVM in processing large-scale data. In addition the soft margin method is proposed to modify the excursion of separation margin and to be effective in the gray zone that the distribution of data becomes hard to be described and the separation margin between classes.

Analyzing Big Data with the Hybrid Interval Regression Methods

PubMed Central

Kao, Han-Ying

2014-01-01

Big data is a new trend at present, forcing the significant impacts on information technologies. In big data applications, one of the most concerned issues is dealing with large-scale data sets that often require computation resources provided by public cloud services. How to analyze big data efficiently becomes a big challenge. In this paper, we collaborate interval regression with the smooth support vector machine (SSVM) to analyze big data. Recently, the smooth support vector machine (SSVM) was proposed as an alternative of the standard SVM that has been proved more efficient than the traditional SVM in processing large-scale data. In addition the soft margin method is proposed to modify the excursion of separation margin and to be effective in the gray zone that the distribution of data becomes hard to be described and the separation margin between classes. PMID:25143968

The fastclime Package for Linear Programming and Large-Scale Precision Matrix Estimation in R.

PubMed

Pang, Haotian; Liu, Han; Vanderbei, Robert

2014-02-01

We develop an R package fastclime for solving a family of regularized linear programming (LP) problems. Our package efficiently implements the parametric simplex algorithm, which provides a scalable and sophisticated tool for solving large-scale linear programs. As an illustrative example, one use of our LP solver is to implement an important sparse precision matrix estimation method called CLIME (Constrained L 1 Minimization Estimator). Compared with existing packages for this problem such as clime and flare, our package has three advantages: (1) it efficiently calculates the full piecewise-linear regularization path; (2) it provides an accurate dual certificate as stopping criterion; (3) it is completely coded in C and is highly portable. This package is designed to be useful to statisticians and machine learning researchers for solving a wide range of problems.

Environmental performance evaluation of large-scale municipal solid waste incinerators using data envelopment analysis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chen, H.-W.; Chang, N.-B., E-mail: nchang@mail.ucf.ed; Chen, J.-C.

2010-07-15

Limited to insufficient land resources, incinerators are considered in many countries such as Japan and Germany as the major technology for a waste management scheme capable of dealing with the increasing demand for municipal and industrial solid waste treatment in urban regions. The evaluation of these municipal incinerators in terms of secondary pollution potential, cost-effectiveness, and operational efficiency has become a new focus in the highly interdisciplinary area of production economics, systems analysis, and waste management. This paper aims to demonstrate the application of data envelopment analysis (DEA) - a production economics tool - to evaluate performance-based efficiencies of 19more » large-scale municipal incinerators in Taiwan with different operational conditions. A 4-year operational data set from 2002 to 2005 was collected in support of DEA modeling using Monte Carlo simulation to outline the possibility distributions of operational efficiency of these incinerators. Uncertainty analysis using the Monte Carlo simulation provides a balance between simplifications of our analysis and the soundness of capturing the essential random features that complicate solid waste management systems. To cope with future challenges, efforts in the DEA modeling, systems analysis, and prediction of the performance of large-scale municipal solid waste incinerators under normal operation and special conditions were directed toward generating a compromised assessment procedure. Our research findings will eventually lead to the identification of the optimal management strategies for promoting the quality of solid waste incineration, not only in Taiwan, but also elsewhere in the world.« less

Shear-driven dynamo waves at high magnetic Reynolds number.

PubMed

Tobias, S M; Cattaneo, F

2013-05-23

Astrophysical magnetic fields often display remarkable organization, despite being generated by dynamo action driven by turbulent flows at high conductivity. An example is the eleven-year solar cycle, which shows spatial coherence over the entire solar surface. The difficulty in understanding the emergence of this large-scale organization is that whereas at low conductivity (measured by the magnetic Reynolds number, Rm) dynamo fields are well organized, at high Rm their structure is dominated by rapidly varying small-scale fluctuations. This arises because the smallest scales have the highest rate of strain, and can amplify magnetic field most efficiently. Therefore most of the effort to find flows whose large-scale dynamo properties persist at high Rm has been frustrated. Here we report high-resolution simulations of a dynamo that can generate organized fields at high Rm; indeed, the generation mechanism, which involves the interaction between helical flows and shear, only becomes effective at large Rm. The shear does not enhance generation at large scales, as is commonly thought; instead it reduces generation at small scales. The solution consists of propagating dynamo waves, whose existence was postulated more than 60 years ago and which have since been used to model the solar cycle.

The Concert system - Compiler and runtime technology for efficient concurrent object-oriented programming

NASA Technical Reports Server (NTRS)

Chien, Andrew A.; Karamcheti, Vijay; Plevyak, John; Sahrawat, Deepak

1993-01-01

Concurrent object-oriented languages, particularly fine-grained approaches, reduce the difficulty of large scale concurrent programming by providing modularity through encapsulation while exposing large degrees of concurrency. Despite these programmability advantages, such languages have historically suffered from poor efficiency. This paper describes the Concert project whose goal is to develop portable, efficient implementations of fine-grained concurrent object-oriented languages. Our approach incorporates aggressive program analysis and program transformation with careful information management at every stage from the compiler to the runtime system. The paper discusses the basic elements of the Concert approach along with a description of the potential payoffs. Initial performance results and specific plans for system development are also detailed.

Application and research of block caving in Pulang copper mine

NASA Astrophysics Data System (ADS)

Ge, Qifa; Fan, Wenlu; Zhu, Weigen; Chen, Xiaowei

2018-01-01

The application of block caving in mines shows significant advantages in large scale, low cost and high efficiency, thus block caving is worth promoting in the mines that meets the requirement of natural caving. Due to large scale of production and low ore grade in Pulang copper mine in China, comprehensive analysis and research were conducted on rock mechanics, mining sequence, undercutting and stability of bottom structure in terms of raising mine benefit and maximizing the recovery mineral resources. Finally this study summarizes that block caving is completely suitable for Pulang copper mine.

A parallel orbital-updating based plane-wave basis method for electronic structure calculations

NASA Astrophysics Data System (ADS)

Pan, Yan; Dai, Xiaoying; de Gironcoli, Stefano; Gong, Xin-Gao; Rignanese, Gian-Marco; Zhou, Aihui

2017-11-01

Motivated by the recently proposed parallel orbital-updating approach in real space method [1], we propose a parallel orbital-updating based plane-wave basis method for electronic structure calculations, for solving the corresponding eigenvalue problems. In addition, we propose two new modified parallel orbital-updating methods. Compared to the traditional plane-wave methods, our methods allow for two-level parallelization, which is particularly interesting for large scale parallelization. Numerical experiments show that these new methods are more reliable and efficient for large scale calculations on modern supercomputers.

Solving Large-Scale Inverse Magnetostatic Problems using the Adjoint Method

PubMed Central

Bruckner, Florian; Abert, Claas; Wautischer, Gregor; Huber, Christian; Vogler, Christoph; Hinze, Michael; Suess, Dieter

2017-01-01

An efficient algorithm for the reconstruction of the magnetization state within magnetic components is presented. The occurring inverse magnetostatic problem is solved by means of an adjoint approach, based on the Fredkin-Koehler method for the solution of the forward problem. Due to the use of hybrid FEM-BEM coupling combined with matrix compression techniques the resulting algorithm is well suited for large-scale problems. Furthermore the reconstruction of the magnetization state within a permanent magnet as well as an optimal design application are demonstrated. PMID:28098851

Scaling up HIV viral load - lessons from the large-scale implementation of HIV early infant diagnosis and CD4 testing.

PubMed

Peter, Trevor; Zeh, Clement; Katz, Zachary; Elbireer, Ali; Alemayehu, Bereket; Vojnov, Lara; Costa, Alex; Doi, Naoko; Jani, Ilesh

2017-11-01

The scale-up of effective HIV viral load (VL) testing is an urgent public health priority. Implementation of testing is supported by the availability of accurate, nucleic acid based laboratory and point-of-care (POC) VL technologies and strong WHO guidance recommending routine testing to identify treatment failure. However, test implementation faces challenges related to the developing health systems in many low-resource countries. The purpose of this commentary is to review the challenges and solutions from the large-scale implementation of other diagnostic tests, namely nucleic-acid based early infant HIV diagnosis (EID) and CD4 testing, and identify key lessons to inform the scale-up of VL. Experience with EID and CD4 testing provides many key lessons to inform VL implementation and may enable more effective and rapid scale-up. The primary lessons from earlier implementation efforts are to strengthen linkage to clinical care after testing, and to improve the efficiency of testing. Opportunities to improve linkage include data systems to support the follow-up of patients through the cascade of care and test delivery, rapid sample referral networks, and POC tests. Opportunities to increase testing efficiency include improvements to procurement and supply chain practices, well connected tiered laboratory networks with rational deployment of test capacity across different levels of health services, routine resource mapping and mobilization to ensure adequate resources for testing programs, and improved operational and quality management of testing services. If applied to VL testing programs, these approaches could help improve the impact of VL on ART failure management and patient outcomes, reduce overall costs and help ensure the sustainable access to reduced pricing for test commodities, as well as improve supportive health systems such as efficient, and more rigorous quality assurance. These lessons draw from traditional laboratory practices as well as fields such as logistics, operations management and business. The lessons and innovations from large-scale EID and CD4 programs described here can be adapted to inform more effective scale-up approaches for VL. They demonstrate that an integrated approach to health system strengthening focusing on key levers for test access such as data systems, supply efficiencies and network management. They also highlight the challenges with implementation and the need for more innovative approaches and effective partnerships to achieve equitable and cost-effective test access. © 2017 The Authors. Journal of the International AIDS Society published by John Wiley & sons Ltd on behalf of the International AIDS Society.

High-Efficiency, Multijunction Solar Cells for Large-Scale Solar Electricity Generation

NASA Astrophysics Data System (ADS)

Kurtz, Sarah

2006-03-01

A solar cell with an infinite number of materials (matched to the solar spectrum) has a theoretical efficiency limit of 68%. If sunlight is concentrated, this limit increases to about 87%. These theoretical limits are calculated using basic physics and are independent of the details of the materials. In practice, the challenge of achieving high efficiency depends on identifying materials that can effectively use the solar spectrum. Impressive progress has been made with the current efficiency record being 39%. Today's solar market is also showing impressive progress, but is still hindered by high prices. One strategy for reducing cost is to use lenses or mirrors to focus the light on small solar cells. In this case, the system cost is dominated by the cost of the relatively inexpensive optics. The value of the optics increases with the efficiency of the solar cell. Thus, a concentrator system made with 35%- 40%-efficient solar cells is expected to deliver 50% more power at a similar cost when compare with a system using 25%-efficient cells. Today's markets are showing an opportunity for large concentrator systems that didn't exist 5-10 years ago. Efficiencies may soon pass 40% and ultimately may reach 50%, providing a pathway to improved performance and decreased cost. Many companies are currently investigating this technology for large-scale electricity generation. The presentation will cover the basic physics and more practical considerations to achieving high efficiency as well as describing the current status of the concentrator industry. This work has been authored by an employee of the Midwest Research Institute under Contract No. DE- AC36-99GO10337 with the U.S. Department of Energy. The United States Government retains and the publisher, by accepting the article for publication, acknowledges that the United States Government retains a non-exclusive, paid-up, irrevocable, worldwide license to publish or reproduce the published form of this work, or allow others to do so, for United States Government purposes.

Improving Public-spending Efficiency in Czech Regions and Municipalities. OECD Economics Department Working Papers, No. 499

ERIC Educational Resources Information Center

Hemmings, Philip

2006-01-01

This paper looks at ways of ensuring Czech regions and municipalities are fully motivated to make efficiency improvements in public service provision and so help achieve countrywide fiscal sustainability. The very large number of small municipalities in the Czech Republic means that scale economies are difficult to exploit and the policy options…

Cascading pressure reactor and method for solar-thermochemical reactions

DOEpatents

Ermanoski, Ivan

2017-11-14

Reactors and methods for solar thermochemical reactions are disclosed. The reactors and methods include a cascade of reduction chambers at successively lower pressures that leads to over an order of magnitude pressure decrease compared to a single-chambered design. The resulting efficiency gains are substantial, and represent an important step toward practical and efficient solar fuel production on a large scale.

A review of challenges to determining and demonstrating efficiency of large fire management

Treesearch

Matthew P. Thompson; Francisco Rodriguez y Silva; David E. Calkin; Michael S. Hand

2017-01-01

Characterising the impacts of wildland fire and fire suppression is critical information for fire management decision-making. Here, we focus on decisions related to the rare larger and longer-duration fire events, where the scope and scale of decision-making can be far broader than initial response efforts, and where determining and demonstrating efficiency of...

Large-scale particle acceleration by magnetic reconnection during solar flares

NASA Astrophysics Data System (ADS)

Li, X.; Guo, F.; Li, H.; Li, G.; Li, S.

2017-12-01

Magnetic reconnection that triggers explosive magnetic energy release has been widely invoked to explain the large-scale particle acceleration during solar flares. While great efforts have been spent in studying the acceleration mechanism in small-scale kinetic simulations, there have been rare studies that make predictions to acceleration in the large scale comparable to the flare reconnection region. Here we present a new arrangement to study this problem. We solve the large-scale energetic-particle transport equation in the fluid velocity and magnetic fields from high-Lundquist-number MHD simulations of reconnection layers. This approach is based on examining the dominant acceleration mechanism and pitch-angle scattering in kinetic simulations. Due to the fluid compression in reconnection outflows and merging magnetic islands, particles are accelerated to high energies and develop power-law energy distributions. We find that the acceleration efficiency and power-law index depend critically on upstream plasma beta and the magnitude of guide field (the magnetic field component perpendicular to the reconnecting component) as they influence the compressibility of the reconnection layer. We also find that the accelerated high-energy particles are mostly concentrated in large magnetic islands, making the islands a source of energetic particles and high-energy emissions. These findings may provide explanations for acceleration process in large-scale magnetic reconnection during solar flares and the temporal and spatial emission properties observed in different flare events.

Development and manufacture of reactive-transfer-printed CIGS photovoltaic modules

NASA Astrophysics Data System (ADS)

Eldada, Louay; Sang, Baosheng; Lu, Dingyuan; Stanbery, Billy J.

2010-09-01

In recent years, thin-film photovoltaic (PV) companies started realizing their low manufacturing cost potential, and grabbing an increasingly larger market share from multicrystalline silicon companies. Copper Indium Gallium Selenide (CIGS) is the most promising thin-film PV material, having demonstrated the highest energy conversion efficiency in both cells and modules. However, most CIGS manufacturers still face the challenge of delivering a reliable and rapid manufacturing process that can scale effectively and deliver on the promise of this material system. HelioVolt has developed a reactive transfer process for CIGS absorber formation that has the benefits of good compositional control, high-quality CIGS grains, and a fast reaction. The reactive transfer process is a two stage CIGS fabrication method. Precursor films are deposited onto substrates and reusable print plates in the first stage, while in the second stage, the CIGS layer is formed by rapid heating with Se confinement. High quality CIGS films with large grains were produced on a full-scale manufacturing line, and resulted in high-efficiency large-form-factor modules. With 14% cell efficiency and 12% module efficiency, HelioVolt started to commercialize the process on its first production line with 20 MW nameplate capacity.

Performance Study of Salt Cavern Air Storage Based Non-Supplementary Fired Compressed Air Energy Storage System

NASA Astrophysics Data System (ADS)

Chen, Xiaotao; Song, Jie; Liang, Lixiao; Si, Yang; Wang, Le; Xue, Xiaodai

2017-10-01

Large-scale energy storage system (ESS) plays an important role in the planning and operation of smart grid and energy internet. Compressed air energy storage (CAES) is one of promising large-scale energy storage techniques. However, the high cost of the storage of compressed air and the low capacity remain to be solved. This paper proposes a novel non-supplementary fired compressed air energy storage system (NSF-CAES) based on salt cavern air storage to address the issues of air storage and the efficiency of CAES. Operating mechanisms of the proposed NSF-CAES are analysed based on thermodynamics principle. Key factors which has impact on the system storage efficiency are thoroughly explored. The energy storage efficiency of the proposed NSF-CAES system can be improved by reducing the maximum working pressure of the salt cavern and improving inlet air pressure of the turbine. Simulation results show that the electric-to-electric conversion efficiency of the proposed NSF-CAES can reach 63.29% with a maximum salt cavern working pressure of 9.5 MPa and 9 MPa inlet air pressure of the turbine, which is higher than the current commercial CAES plants.

Extracting Communities from Complex Networks by the k-Dense Method

NASA Astrophysics Data System (ADS)

Saito, Kazumi; Yamada, Takeshi; Kazama, Kazuhiro

To understand the structural and functional properties of large-scale complex networks, it is crucial to efficiently extract a set of cohesive subnetworks as communities. There have been proposed several such community extraction methods in the literature, including the classical k-core decomposition method and, more recently, the k-clique based community extraction method. The k-core method, although computationally efficient, is often not powerful enough for uncovering a detailed community structure and it produces only coarse-grained and loosely connected communities. The k-clique method, on the other hand, can extract fine-grained and tightly connected communities but requires a substantial amount of computational load for large-scale complex networks. In this paper, we present a new notion of a subnetwork called k-dense, and propose an efficient algorithm for extracting k-dense communities. We applied our method to the three different types of networks assembled from real data, namely, from blog trackbacks, word associations and Wikipedia references, and demonstrated that the k-dense method could extract communities almost as efficiently as the k-core method, while the qualities of the extracted communities are comparable to those obtained by the k-clique method.

Scaling of electromagnetic transducers for shunt damping and energy harvesting

NASA Astrophysics Data System (ADS)

Elliott, Stephen J.; Zilletti, Michele

2014-04-01

In order for an electromagnetic transducer to operate well as either a mechanical shunt damper or as a vibration energy harvester, it must have good electromechanical coupling. A simple two-port analysis is used to derive a non-dimensional measure of electromechanical coupling, which must be large compared with unity for efficient operation in both of these applications. The two-port parameters for an inertial electromagnetic transducer are derived, from which this non-dimensional coupling parameter can be evaluated. The largest value that this parameter takes is approximately equal to the square of the magnetic flux density times the length of wire in the field, divided by the mechanical damping times the electrical resistance. This parameter is found to be only of the order of one for voice coil devices that weigh approximately 1 kg, and so such devices are generally not efficient, within the definition used here, in either of these applications. The non-dimensional coupling parameter is found to scale in approximate proportion to the device's characteristic length, however, and so although miniaturised devices are less efficient, greater efficiency can be obtained with large devices, such as those used to control civil engineering structures.

Concentrating light in Cu(In,Ga)Se2 solar cells

NASA Astrophysics Data System (ADS)

Schmid, M.; Yin, G.; Song, M.; Duan, S.; Heidmann, B.; Sancho-Martinez, D.; Kämmer, S.; Köhler, T.; Manley, P.; Lux-Steiner, M. Ch.

2016-09-01

Light concentration has proven beneficial for solar cells, most notably for highly efficient but expensive absorber materials using high concentrations and large scale optics. Here we investigate light concentration for cost efficient thinfilm solar cells which show nano- or microtextured absorbers. Our absorber material of choice is Cu(In,Ga)Se2 (CIGSe) which has a proven stabilized record efficiency of 22.6% and which - despite being a polycrystalline thin-film material - is very tolerant to environmental influences. Taking a nanoscale approach, we concentrate light in the CIGSe absorber layer by integrating photonic nanostructures made from dielectric materials. The dielectric nanostructures give rise to resonant modes and field localization in their vicinity. Thus when inserted inside or adjacent to the absorber layer, absorption and efficiency enhancement are observed. In contrast to this internal absorption enhancement, external enhancement is exploited in the microscale approach: mm-sized lenses can be used to concentrate light onto CIGSe solar cells with lateral dimensions reduced down to the micrometer range. These micro solar cells come with the benefit of improved heat dissipation compared to the large scale concentrators and promise compact high efficiency devices. Both approaches of light concentration allow for reduction in material consumption by restricting the absorber dimension either vertically (ultra-thin absorbers for dielectric nanostructures) or horizontally (micro absorbers for concentrating lenses) and have significant potential for efficiency enhancement.

Concentrating light in Cu(In,Ga)Se2 solar cells

NASA Astrophysics Data System (ADS)

Schmid, Martina; Yin, Guanchao; Song, Min; Duan, Shengkai; Heidmann, Berit; Sancho-Martinez, Diego; Kämmer, Steven; Köhler, Tristan; Manley, Phillip; Lux-Steiner, Martha Ch.

2017-01-01

Light concentration has proven beneficial for solar cells, most notably for highly efficient but expensive absorber materials using high concentrations and large scale optics. Here, we investigate the light concentration for cost-efficient thin-film solar cells that show nano- or microtextured absorbers. Our absorber material of choice is Cu(In,Ga)Se2 (CIGSe), which has a proven stabilized record efficiency of 22.6% and which-despite being a polycrystalline thin-film material-is very tolerant to environmental influences. Taking a nanoscale approach, we concentrate light in the CIGSe absorber layer by integrating photonic nanostructures made from dielectric materials. The dielectric nanostructures give rise to resonant modes and field localization in their vicinity. Thus, when inserted inside or adjacent to the absorber layer, absorption and efficiency enhancement are observed. In contrast to this internal absorption enhancement, external enhancement is exploited in the microscaled approach: mm-sized lenses can be used to concentrate light onto CIGSe solar cells with lateral dimensions reduced down to the micrometer range. These micro solar cells come with the benefit of improved heat dissipation compared with the large scale concentrators and promise compact high-efficiency devices. Both approaches of light concentration allow for reduction in material consumption by restricting the absorber dimension either vertically (ultrathin absorbers for dielectric nanostructures) or horizontally (microabsorbers for concentrating lenses) and have significant potential for efficiency enhancement.

Analysis and optimization of gyrokinetic toroidal simulations on homogenous and heterogenous platforms

DOE PAGES

Ibrahim, Khaled Z.; Madduri, Kamesh; Williams, Samuel; ...

2013-07-18

The Gyrokinetic Toroidal Code (GTC) uses the particle-in-cell method to efficiently simulate plasma microturbulence. This paper presents novel analysis and optimization techniques to enhance the performance of GTC on large-scale machines. We introduce cell access analysis to better manage locality vs. synchronization tradeoffs on CPU and GPU-based architectures. Finally, our optimized hybrid parallel implementation of GTC uses MPI, OpenMP, and NVIDIA CUDA, achieves up to a 2× speedup over the reference Fortran version on multiple parallel systems, and scales efficiently to tens of thousands of cores.

SparseMaps—A systematic infrastructure for reduced-scaling electronic structure methods. III. Linear-scaling multireference domain-based pair natural orbital N-electron valence perturbation theory

NASA Astrophysics Data System (ADS)

Guo, Yang; Sivalingam, Kantharuban; Valeev, Edward F.; Neese, Frank

2016-03-01

Multi-reference (MR) electronic structure methods, such as MR configuration interaction or MR perturbation theory, can provide reliable energies and properties for many molecular phenomena like bond breaking, excited states, transition states or magnetic properties of transition metal complexes and clusters. However, owing to their inherent complexity, most MR methods are still too computationally expensive for large systems. Therefore the development of more computationally attractive MR approaches is necessary to enable routine application for large-scale chemical systems. Among the state-of-the-art MR methods, second-order N-electron valence state perturbation theory (NEVPT2) is an efficient, size-consistent, and intruder-state-free method. However, there are still two important bottlenecks in practical applications of NEVPT2 to large systems: (a) the high computational cost of NEVPT2 for large molecules, even with moderate active spaces and (b) the prohibitive cost for treating large active spaces. In this work, we address problem (a) by developing a linear scaling "partially contracted" NEVPT2 method. This development uses the idea of domain-based local pair natural orbitals (DLPNOs) to form a highly efficient algorithm. As shown previously in the framework of single-reference methods, the DLPNO concept leads to an enormous reduction in computational effort while at the same time providing high accuracy (approaching 99.9% of the correlation energy), robustness, and black-box character. In the DLPNO approach, the virtual space is spanned by pair natural orbitals that are expanded in terms of projected atomic orbitals in large orbital domains, while the inactive space is spanned by localized orbitals. The active orbitals are left untouched. Our implementation features a highly efficient "electron pair prescreening" that skips the negligible inactive pairs. The surviving pairs are treated using the partially contracted NEVPT2 formalism. A detailed comparison between the partial and strong contraction schemes is made, with conclusions that discourage the strong contraction scheme as a basis for local correlation methods due to its non-invariance with respect to rotations in the inactive and external subspaces. A minimal set of conservatively chosen truncation thresholds controls the accuracy of the method. With the default thresholds, about 99.9% of the canonical partially contracted NEVPT2 correlation energy is recovered while the crossover of the computational cost with the already very efficient canonical method occurs reasonably early; in linear chain type compounds at a chain length of around 80 atoms. Calculations are reported for systems with more than 300 atoms and 5400 basis functions.

Methods comparison for microsatellite marker development: Different isolation methods, different yield efficiency

NASA Astrophysics Data System (ADS)

Zhan, Aibin; Bao, Zhenmin; Hu, Xiaoli; Lu, Wei; Hu, Jingjie

2009-06-01

Microsatellite markers have become one kind of the most important molecular tools used in various researches. A large number of microsatellite markers are required for the whole genome survey in the fields of molecular ecology, quantitative genetics and genomics. Therefore, it is extremely necessary to select several versatile, low-cost, efficient and time- and labor-saving methods to develop a large panel of microsatellite markers. In this study, we used Zhikong scallop ( Chlamys farreri) as the target species to compare the efficiency of the five methods derived from three strategies for microsatellite marker development. The results showed that the strategy of constructing small insert genomic DNA library resulted in poor efficiency, while the microsatellite-enriched strategy highly improved the isolation efficiency. Although the mining public database strategy is time- and cost-saving, it is difficult to obtain a large number of microsatellite markers, mainly due to the limited sequence data of non-model species deposited in public databases. Based on the results in this study, we recommend two methods, microsatellite-enriched library construction method and FIASCO-colony hybridization method, for large-scale microsatellite marker development. Both methods were derived from the microsatellite-enriched strategy. The experimental results obtained from Zhikong scallop also provide the reference for microsatellite marker development in other species with large genomes.

Efficiency equations of the railgun

NASA Astrophysics Data System (ADS)

Sadedin, D. R.

1984-03-01

The feasibility of an employment of railguns for large scale applications, such as space launching, will ultimately be determined by efficiency considerations. The present investigation is concerned with the calculation of the efficiencies for constant current railguns. Elementary considerations are discussed, taking into account a simple condition for high efficiency, the magnetic field of the rails, and the acceleration force on the projectile. The loss in a portion of the rails is considered along with rail loss comparisons, applications to the segmented gun, rail losses related to the constant resistance per unit length, efficiency expressions, and arc, or muzzle voltage energy.

Potential gains from hospital mergers in Denmark.

PubMed

Kristensen, Troels; Bogetoft, Peter; Pedersen, Kjeld Moeller

2010-12-01

The Danish hospital sector faces a major rebuilding program to centralize activity in fewer and larger hospitals. We aim to conduct an efficiency analysis of hospitals and to estimate the potential cost savings from the planned hospital mergers. We use Data Envelopment Analysis (DEA) to estimate a cost frontier. Based on this analysis, we calculate an efficiency score for each hospital and estimate the potential gains from the proposed mergers by comparing individual efficiencies with the efficiency of the combined hospitals. Furthermore, we apply a decomposition algorithm to split merger gains into technical efficiency, size (scale) and harmony (mix) gains. The motivation for this decomposition is that some of the apparent merger gains may actually be available with less than a full-scale merger, e.g., by sharing best practices and reallocating certain resources and tasks. Our results suggest that many hospitals are technically inefficient, and the expected "best practice" hospitals are quite efficient. Also, some mergers do not seem to lower costs. This finding indicates that some merged hospitals become too large and therefore experience diseconomies of scale. Other mergers lead to considerable cost reductions; we find potential gains resulting from learning better practices and the exploitation of economies of scope. To ensure robustness, we conduct a sensitivity analysis using two alternative returns-to-scale assumptions and two alternative estimation approaches. We consistently find potential gains from improving the technical efficiency and the exploitation of economies of scope from mergers.

An accurate and computationally efficient algorithm for ground peak identification in large footprint waveform LiDAR data

NASA Astrophysics Data System (ADS)

Zhuang, Wei; Mountrakis, Giorgos

2014-09-01

Large footprint waveform LiDAR sensors have been widely used for numerous airborne studies. Ground peak identification in a large footprint waveform is a significant bottleneck in exploring full usage of the waveform datasets. In the current study, an accurate and computationally efficient algorithm was developed for ground peak identification, called Filtering and Clustering Algorithm (FICA). The method was evaluated on Land, Vegetation, and Ice Sensor (LVIS) waveform datasets acquired over Central NY. FICA incorporates a set of multi-scale second derivative filters and a k-means clustering algorithm in order to avoid detecting false ground peaks. FICA was tested in five different land cover types (deciduous trees, coniferous trees, shrub, grass and developed area) and showed more accurate results when compared to existing algorithms. More specifically, compared with Gaussian decomposition, the RMSE ground peak identification by FICA was 2.82 m (5.29 m for GD) in deciduous plots, 3.25 m (4.57 m for GD) in coniferous plots, 2.63 m (2.83 m for GD) in shrub plots, 0.82 m (0.93 m for GD) in grass plots, and 0.70 m (0.51 m for GD) in plots of developed areas. FICA performance was also relatively consistent under various slope and canopy coverage (CC) conditions. In addition, FICA showed better computational efficiency compared to existing methods. FICA's major computational and accuracy advantage is a result of the adopted multi-scale signal processing procedures that concentrate on local portions of the signal as opposed to the Gaussian decomposition that uses a curve-fitting strategy applied in the entire signal. The FICA algorithm is a good candidate for large-scale implementation on future space-borne waveform LiDAR sensors.

Relay discovery and selection for large-scale P2P streaming

PubMed Central

Zhang, Chengwei; Wang, Angela Yunxian

2017-01-01

In peer-to-peer networks, application relays have been commonly used to provide various networking services. The service performance often improves significantly if a relay is selected appropriately based on its network location. In this paper, we studied the location-aware relay discovery and selection problem for large-scale P2P streaming networks. In these large-scale and dynamic overlays, it incurs significant communication and computation cost to discover a sufficiently large relay candidate set and further to select one relay with good performance. The network location can be measured directly or indirectly with the tradeoffs between timeliness, overhead and accuracy. Based on a measurement study and the associated error analysis, we demonstrate that indirect measurements, such as King and Internet Coordinate Systems (ICS), can only achieve a coarse estimation of peers’ network location and those methods based on pure indirect measurements cannot lead to a good relay selection. We also demonstrate that there exists significant error amplification of the commonly used “best-out-of-K” selection methodology using three RTT data sets publicly available. We propose a two-phase approach to achieve efficient relay discovery and accurate relay selection. Indirect measurements are used to narrow down a small number of high-quality relay candidates and the final relay selection is refined based on direct probing. This two-phase approach enjoys an efficient implementation using the Distributed-Hash-Table (DHT). When the DHT is constructed, the node keys carry the location information and they are generated scalably using indirect measurements, such as the ICS coordinates. The relay discovery is achieved efficiently utilizing the DHT-based search. We evaluated various aspects of this DHT-based approach, including the DHT indexing procedure, key generation under peer churn and message costs. PMID:28410384

Relay discovery and selection for large-scale P2P streaming.

PubMed

Zhang, Chengwei; Wang, Angela Yunxian; Hei, Xiaojun

2017-01-01

In peer-to-peer networks, application relays have been commonly used to provide various networking services. The service performance often improves significantly if a relay is selected appropriately based on its network location. In this paper, we studied the location-aware relay discovery and selection problem for large-scale P2P streaming networks. In these large-scale and dynamic overlays, it incurs significant communication and computation cost to discover a sufficiently large relay candidate set and further to select one relay with good performance. The network location can be measured directly or indirectly with the tradeoffs between timeliness, overhead and accuracy. Based on a measurement study and the associated error analysis, we demonstrate that indirect measurements, such as King and Internet Coordinate Systems (ICS), can only achieve a coarse estimation of peers' network location and those methods based on pure indirect measurements cannot lead to a good relay selection. We also demonstrate that there exists significant error amplification of the commonly used "best-out-of-K" selection methodology using three RTT data sets publicly available. We propose a two-phase approach to achieve efficient relay discovery and accurate relay selection. Indirect measurements are used to narrow down a small number of high-quality relay candidates and the final relay selection is refined based on direct probing. This two-phase approach enjoys an efficient implementation using the Distributed-Hash-Table (DHT). When the DHT is constructed, the node keys carry the location information and they are generated scalably using indirect measurements, such as the ICS coordinates. The relay discovery is achieved efficiently utilizing the DHT-based search. We evaluated various aspects of this DHT-based approach, including the DHT indexing procedure, key generation under peer churn and message costs.

ATLAS and LHC computing on CRAY

NASA Astrophysics Data System (ADS)

Sciacca, F. G.; Haug, S.; ATLAS Collaboration

2017-10-01

Access and exploitation of large scale computing resources, such as those offered by general purpose HPC centres, is one important measure for ATLAS and the other Large Hadron Collider experiments in order to meet the challenge posed by the full exploitation of the future data within the constraints of flat budgets. We report on the effort of moving the Swiss WLCG T2 computing, serving ATLAS, CMS and LHCb, from a dedicated cluster to the large Cray systems at the Swiss National Supercomputing Centre CSCS. These systems do not only offer very efficient hardware, cooling and highly competent operators, but also have large backfill potentials due to size and multidisciplinary usage and potential gains due to economy at scale. Technical solutions, performance, expected return and future plans are discussed.

Why do Scale-Free Networks Emerge in Nature? From Gradient Networks to Transport Efficiency

NASA Astrophysics Data System (ADS)

Toroczkai, Zoltan

2004-03-01

It has recently been recognized [1,2,3] that a large number of complex networks are scale-free (having a power-law degree distribution). Examples include citation networks [4], the internet [5], the world-wide-web [6], cellular metabolic networks [7], protein interaction networks [8], the sex-web [9] and alliance networks in the U.S. biotechnology industry [10]. The existence of scale-free networks in such diverse systems suggests that there is a simple underlying common reason for their development. Here, we propose that scale-free networks emerge because they ensure efficient transport of some entity. We show that for flows generated by gradients of a scalar "potential'' distributed on a network, non scale-free networks, e.g., random graphs [11], will become maximally congested, while scale-free networks will ensure efficient transport in the large network size limit. [1] R. Albert and A.-L. Barabási, Rev.Mod.Phys. 74, 47 (2002). [2] M.E.J. Newman, SIAM Rev. 45, 167 (2003). [3] S.N. Dorogovtsev and J.F.F. Mendes, Evolution of Networks: From Biological Nets to the Internet and WWW, Oxford Univ. Press, Oxford, 2003. [4] S. Redner, Eur.Phys.J. B, 4, 131 (1998). [5] M. Faloutsos, P. Faloutsos and C. Faloutsos Comp.Comm.Rev. 29, 251 (1999). [6] R. Albert, H. Jeong, and A.L. Barabási, Nature 401, 130 (1999). [7] H. Jeong et.al. Nature 407, 651 (2000). [8] H. Jeong, S. Mason, A.-L. Barabási and Z. N. Oltvai, Nature 411, 41 (2001). [9] F. Liljeros et. al. Nature 411 907 (2000). [10] W. W. Powell, D. R. White, K. W. Koput and J. Owen-Smith Am.J.Soc. in press. [11] B. Bollobás, Random Graphs, Second Edition, Cambridge University Press (2001).

Quantifying aggregated uncertainty in Plasmodium falciparum malaria prevalence and populations at risk via efficient space-time geostatistical joint simulation.

PubMed

Gething, Peter W; Patil, Anand P; Hay, Simon I

2010-04-01

Risk maps estimating the spatial distribution of infectious diseases are required to guide public health policy from local to global scales. The advent of model-based geostatistics (MBG) has allowed these maps to be generated in a formal statistical framework, providing robust metrics of map uncertainty that enhances their utility for decision-makers. In many settings, decision-makers require spatially aggregated measures over large regions such as the mean prevalence within a country or administrative region, or national populations living under different levels of risk. Existing MBG mapping approaches provide suitable metrics of local uncertainty--the fidelity of predictions at each mapped pixel--but have not been adapted for measuring uncertainty over large areas, due largely to a series of fundamental computational constraints. Here the authors present a new efficient approximating algorithm that can generate for the first time the necessary joint simulation of prevalence values across the very large prediction spaces needed for global scale mapping. This new approach is implemented in conjunction with an established model for P. falciparum allowing robust estimates of mean prevalence at any specified level of spatial aggregation. The model is used to provide estimates of national populations at risk under three policy-relevant prevalence thresholds, along with accompanying model-based measures of uncertainty. By overcoming previously unchallenged computational barriers, this study illustrates how MBG approaches, already at the forefront of infectious disease mapping, can be extended to provide large-scale aggregate measures appropriate for decision-makers.

Exploring Google Earth Engine platform for big data processing: classification of multi-temporal satellite imagery for crop mapping

NASA Astrophysics Data System (ADS)

Shelestov, Andrii; Lavreniuk, Mykola; Kussul, Nataliia; Novikov, Alexei; Skakun, Sergii

2017-02-01

Many applied problems arising in agricultural monitoring and food security require reliable crop maps at national or global scale. Large scale crop mapping requires processing and management of large amount of heterogeneous satellite imagery acquired by various sensors that consequently leads to a “Big Data” problem. The main objective of this study is to explore efficiency of using the Google Earth Engine (GEE) platform when classifying multi-temporal satellite imagery with potential to apply the platform for a larger scale (e.g. country level) and multiple sensors (e.g. Landsat-8 and Sentinel-2). In particular, multiple state-of-the-art classifiers available in the GEE platform are compared to produce a high resolution (30 m) crop classification map for a large territory ( 28,100 km2 and 1.0 M ha of cropland). Though this study does not involve large volumes of data, it does address efficiency of the GEE platform to effectively execute complex workflows of satellite data processing required with large scale applications such as crop mapping. The study discusses strengths and weaknesses of classifiers, assesses accuracies that can be achieved with different classifiers for the Ukrainian landscape, and compares them to the benchmark classifier using a neural network approach that was developed in our previous studies. The study is carried out for the Joint Experiment of Crop Assessment and Monitoring (JECAM) test site in Ukraine covering the Kyiv region (North of Ukraine) in 2013. We found that Google Earth Engine (GEE) provides very good performance in terms of enabling access to the remote sensing products through the cloud platform and providing pre-processing; however, in terms of classification accuracy, the neural network based approach outperformed support vector machine (SVM), decision tree and random forest classifiers available in GEE.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rubel, Oliver; Loring, Burlen; Vay, Jean -Luc

The generation of short pulses of ion beams through the interaction of an intense laser with a plasma sheath offers the possibility of compact and cheaper ion sources for many applications--from fast ignition and radiography of dense targets to hadron therapy and injection into conventional accelerators. To enable the efficient analysis of large-scale, high-fidelity particle accelerator simulations using the Warp simulation suite, the authors introduce the Warp In situ Visualization Toolkit (WarpIV). WarpIV integrates state-of-the-art in situ visualization and analysis using VisIt with Warp, supports management and control of complex in situ visualization and analysis workflows, and implements integrated analyticsmore » to facilitate query- and feature-based data analytics and efficient large-scale data analysis. WarpIV enables for the first time distributed parallel, in situ visualization of the full simulation data using high-performance compute resources as the data is being generated by Warp. The authors describe the application of WarpIV to study and compare large 2D and 3D ion accelerator simulations, demonstrating significant differences in the acceleration process in 2D and 3D simulations. WarpIV is available to the public via https://bitbucket.org/berkeleylab/warpiv. The Warp In situ Visualization Toolkit (WarpIV) supports large-scale, parallel, in situ visualization and analysis and facilitates query- and feature-based analytics, enabling for the first time high-performance analysis of large-scale, high-fidelity particle accelerator simulations while the data is being generated by the Warp simulation suite. Furthermore, this supplemental material https://extras.computer.org/extra/mcg2016030022s1.pdf provides more details regarding the memory profiling and optimization and the Yee grid recentering optimization results discussed in the main article.« less

WarpIV: In situ visualization and analysis of ion accelerator simulations

DOE PAGES

Rubel, Oliver; Loring, Burlen; Vay, Jean -Luc; ...

2016-05-09

The generation of short pulses of ion beams through the interaction of an intense laser with a plasma sheath offers the possibility of compact and cheaper ion sources for many applications--from fast ignition and radiography of dense targets to hadron therapy and injection into conventional accelerators. To enable the efficient analysis of large-scale, high-fidelity particle accelerator simulations using the Warp simulation suite, the authors introduce the Warp In situ Visualization Toolkit (WarpIV). WarpIV integrates state-of-the-art in situ visualization and analysis using VisIt with Warp, supports management and control of complex in situ visualization and analysis workflows, and implements integrated analyticsmore » to facilitate query- and feature-based data analytics and efficient large-scale data analysis. WarpIV enables for the first time distributed parallel, in situ visualization of the full simulation data using high-performance compute resources as the data is being generated by Warp. The authors describe the application of WarpIV to study and compare large 2D and 3D ion accelerator simulations, demonstrating significant differences in the acceleration process in 2D and 3D simulations. WarpIV is available to the public via https://bitbucket.org/berkeleylab/warpiv. The Warp In situ Visualization Toolkit (WarpIV) supports large-scale, parallel, in situ visualization and analysis and facilitates query- and feature-based analytics, enabling for the first time high-performance analysis of large-scale, high-fidelity particle accelerator simulations while the data is being generated by the Warp simulation suite. Furthermore, this supplemental material https://extras.computer.org/extra/mcg2016030022s1.pdf provides more details regarding the memory profiling and optimization and the Yee grid recentering optimization results discussed in the main article.« less

Sachem: a chemical cartridge for high-performance substructure search.

PubMed

Kratochvíl, Miroslav; Vondrášek, Jiří; Galgonek, Jakub

2018-05-23

Structure search is one of the valuable capabilities of small-molecule databases. Fingerprint-based screening methods are usually employed to enhance the search performance by reducing the number of calls to the verification procedure. In substructure search, fingerprints are designed to capture important structural aspects of the molecule to aid the decision about whether the molecule contains a given substructure. Currently available cartridges typically provide acceptable search performance for processing user queries, but do not scale satisfactorily with dataset size. We present Sachem, a new open-source chemical cartridge that implements two substructure search methods: The first is a performance-oriented reimplementation of substructure indexing based on the OrChem fingerprint, and the second is a novel method that employs newly designed fingerprints stored in inverted indices. We assessed the performance of both methods on small, medium, and large datasets containing 1, 10, and 94 million compounds, respectively. Comparison of Sachem with other freely available cartridges revealed improvements in overall performance, scaling potential and screen-out efficiency. The Sachem cartridge allows efficient substructure searches in databases of all sizes. The sublinear performance scaling of the second method and the ability to efficiently query large amounts of pre-extracted information may together open the door to new applications for substructure searches.

Mobility Data Analytics Center.

DOT National Transportation Integrated Search

2016-01-01

Mobility Data Analytics Center aims at building a centralized data engine to efficiently manipulate : large-scale data for smart decision making. Integrating and learning the massive data are the key to : the data engine. The ultimate goal of underst...

Multiresource inventories incorporating GIS, GPS, and database management systems

Treesearch

Loukas G. Arvanitis; Balaji Ramachandran; Daniel P. Brackett; Hesham Abd-El Rasol; Xuesong Du

2000-01-01

Large-scale natural resource inventories generate enormous data sets. Their effective handling requires a sophisticated database management system. Such a system must be robust enough to efficiently store large amounts of data and flexible enough to allow users to manipulate a wide variety of information. In a pilot project, related to a multiresource inventory of the...

Electricity's Future: The Shift to Efficiency and Small-Scale Power. Worldwatch Paper 61.

ERIC Educational Resources Information Center

Flavin, Christopher

Electricity, which has largely supplanted oil as the most controversial energy issue of the 1980s, is at the center of some of the world's bitterest economic and environmental controversies. Soaring costs, high interest rates, and environmental damage caused by large power plants have wreaked havoc on the once booming electricity industry.…

Behaviors of susceptible-infected epidemics on scale-free networks with identical infectivity

NASA Astrophysics Data System (ADS)

Zhou, Tao; Liu, Jian-Guo; Bai, Wen-Jie; Chen, Guanrong; Wang, Bing-Hong

2006-11-01

In this paper, we propose a susceptible-infected model with identical infectivity, in which, at every time step, each node can only contact a constant number of neighbors. We implemented this model on scale-free networks, and found that the infected population grows in an exponential form with the time scale proportional to the spreading rate. Furthermore, by numerical simulation, we demonstrated that the targeted immunization of the present model is much less efficient than that of the standard susceptible-infected model. Finally, we investigate a fast spreading strategy when only local information is available. Different from the extensively studied path-finding strategy, the strategy preferring small-degree nodes is more efficient than that preferring large-degree nodes. Our results indicate the existence of an essential relationship between network traffic and network epidemic on scale-free networks.

The morphing of geographical features by Fourier transformation

PubMed Central

Liu, Pengcheng; Yu, Wenhao; Cheng, Xiaoqiang

2018-01-01

This paper presents a morphing model of vector geographical data based on Fourier transformation. This model involves three main steps. They are conversion from vector data to Fourier series, generation of intermediate function by combination of the two Fourier series concerning a large scale and a small scale, and reverse conversion from combination function to vector data. By mirror processing, the model can also be used for morphing of linear features. Experimental results show that this method is sensitive to scale variations and it can be used for vector map features’ continuous scale transformation. The efficiency of this model is linearly related to the point number of shape boundary and the interceptive value n of Fourier expansion. The effect of morphing by Fourier transformation is plausible and the efficiency of the algorithm is acceptable. PMID:29351344

New Distributed Multipole Methods for Accurate Electrostatics for Large-Scale Biomolecular Simultations

NASA Astrophysics Data System (ADS)

Sagui, Celeste

2006-03-01

An accurate and numerically efficient treatment of electrostatics is essential for biomolecular simulations, as this stabilizes much of the delicate 3-d structure associated with biomolecules. Currently, force fields such as AMBER and CHARMM assign ``partial charges'' to every atom in a simulation in order to model the interatomic electrostatic forces, so that the calculation of the electrostatics rapidly becomes the computational bottleneck in large-scale simulations. There are two main issues associated with the current treatment of classical electrostatics: (i) how does one eliminate the artifacts associated with the point-charges (e.g., the underdetermined nature of the current RESP fitting procedure for large, flexible molecules) used in the force fields in a physically meaningful way? (ii) how does one efficiently simulate the very costly long-range electrostatic interactions? Recently, we have dealt with both of these challenges as follows. In order to improve the description of the molecular electrostatic potentials (MEPs), a new distributed multipole analysis based on localized functions -- Wannier, Boys, and Edminston-Ruedenberg -- was introduced, which allows for a first principles calculation of the partial charges and multipoles. Through a suitable generalization of the particle mesh Ewald (PME) and multigrid method, one can treat electrostatic multipoles all the way to hexadecapoles all without prohibitive extra costs. The importance of these methods for large-scale simulations will be discussed, and examplified by simulations from polarizable DNA models.

Developing eThread pipeline using SAGA-pilot abstraction for large-scale structural bioinformatics.

PubMed

Ragothaman, Anjani; Boddu, Sairam Chowdary; Kim, Nayong; Feinstein, Wei; Brylinski, Michal; Jha, Shantenu; Kim, Joohyun

2014-01-01

While most of computational annotation approaches are sequence-based, threading methods are becoming increasingly attractive because of predicted structural information that could uncover the underlying function. However, threading tools are generally compute-intensive and the number of protein sequences from even small genomes such as prokaryotes is large typically containing many thousands, prohibiting their application as a genome-wide structural systems biology tool. To leverage its utility, we have developed a pipeline for eThread--a meta-threading protein structure modeling tool, that can use computational resources efficiently and effectively. We employ a pilot-based approach that supports seamless data and task-level parallelism and manages large variation in workload and computational requirements. Our scalable pipeline is deployed on Amazon EC2 and can efficiently select resources based upon task requirements. We present runtime analysis to characterize computational complexity of eThread and EC2 infrastructure. Based on results, we suggest a pathway to an optimized solution with respect to metrics such as time-to-solution or cost-to-solution. Our eThread pipeline can scale to support a large number of sequences and is expected to be a viable solution for genome-scale structural bioinformatics and structure-based annotation, particularly, amenable for small genomes such as prokaryotes. The developed pipeline is easily extensible to other types of distributed cyberinfrastructure.

Developing eThread Pipeline Using SAGA-Pilot Abstraction for Large-Scale Structural Bioinformatics

PubMed Central

Ragothaman, Anjani; Feinstein, Wei; Jha, Shantenu; Kim, Joohyun

2014-01-01

While most of computational annotation approaches are sequence-based, threading methods are becoming increasingly attractive because of predicted structural information that could uncover the underlying function. However, threading tools are generally compute-intensive and the number of protein sequences from even small genomes such as prokaryotes is large typically containing many thousands, prohibiting their application as a genome-wide structural systems biology tool. To leverage its utility, we have developed a pipeline for eThread—a meta-threading protein structure modeling tool, that can use computational resources efficiently and effectively. We employ a pilot-based approach that supports seamless data and task-level parallelism and manages large variation in workload and computational requirements. Our scalable pipeline is deployed on Amazon EC2 and can efficiently select resources based upon task requirements. We present runtime analysis to characterize computational complexity of eThread and EC2 infrastructure. Based on results, we suggest a pathway to an optimized solution with respect to metrics such as time-to-solution or cost-to-solution. Our eThread pipeline can scale to support a large number of sequences and is expected to be a viable solution for genome-scale structural bioinformatics and structure-based annotation, particularly, amenable for small genomes such as prokaryotes. The developed pipeline is easily extensible to other types of distributed cyberinfrastructure. PMID:24995285

Improved regional-scale Brazilian cropping systems' mapping based on a semi-automatic object-based clustering approach

NASA Astrophysics Data System (ADS)

Bellón, Beatriz; Bégué, Agnès; Lo Seen, Danny; Lebourgeois, Valentine; Evangelista, Balbino Antônio; Simões, Margareth; Demonte Ferraz, Rodrigo Peçanha

2018-06-01

Cropping systems' maps at fine scale over large areas provide key information for further agricultural production and environmental impact assessments, and thus represent a valuable tool for effective land-use planning. There is, therefore, a growing interest in mapping cropping systems in an operational manner over large areas, and remote sensing approaches based on vegetation index time series analysis have proven to be an efficient tool. However, supervised pixel-based approaches are commonly adopted, requiring resource consuming field campaigns to gather training data. In this paper, we present a new object-based unsupervised classification approach tested on an annual MODIS 16-day composite Normalized Difference Vegetation Index time series and a Landsat 8 mosaic of the State of Tocantins, Brazil, for the 2014-2015 growing season. Two variants of the approach are compared: an hyperclustering approach, and a landscape-clustering approach involving a previous stratification of the study area into landscape units on which the clustering is then performed. The main cropping systems of Tocantins, characterized by the crop types and cropping patterns, were efficiently mapped with the landscape-clustering approach. Results show that stratification prior to clustering significantly improves the classification accuracies for underrepresented and sparsely distributed cropping systems. This study illustrates the potential of unsupervised classification for large area cropping systems' mapping and contributes to the development of generic tools for supporting large-scale agricultural monitoring across regions.

Universal nonlinear small-scale dynamo.

PubMed

Beresnyak, A

2012-01-20

We consider astrophysically relevant nonlinear MHD dynamo at large Reynolds numbers (Re). We argue that it is universal in a sense that magnetic energy grows at a rate which is a constant fraction C(E) of the total turbulent dissipation rate. On the basis of locality bounds we claim that this "efficiency of the small-scale dynamo", C(E), is a true constant for large Re and is determined only by strongly nonlinear dynamics at the equipartition scale. We measured C(E) in numerical simulations and observed a value around 0.05 in the highest resolution simulations. We address the issue of C(E) being small, unlike the Kolmogorov constant which is of order unity. © 2012 American Physical Society

Chebyshev polynomial filtered subspace iteration in the discontinuous Galerkin method for large-scale electronic structure calculations

DOE PAGES

Banerjee, Amartya S.; Lin, Lin; Hu, Wei; ...

2016-10-21

The Discontinuous Galerkin (DG) electronic structure method employs an adaptive local basis (ALB) set to solve the Kohn-Sham equations of density functional theory in a discontinuous Galerkin framework. The adaptive local basis is generated on-the-fly to capture the local material physics and can systematically attain chemical accuracy with only a few tens of degrees of freedom per atom. A central issue for large-scale calculations, however, is the computation of the electron density (and subsequently, ground state properties) from the discretized Hamiltonian in an efficient and scalable manner. We show in this work how Chebyshev polynomial filtered subspace iteration (CheFSI) canmore » be used to address this issue and push the envelope in large-scale materials simulations in a discontinuous Galerkin framework. We describe how the subspace filtering steps can be performed in an efficient and scalable manner using a two-dimensional parallelization scheme, thanks to the orthogonality of the DG basis set and block-sparse structure of the DG Hamiltonian matrix. The on-the-fly nature of the ALB functions requires additional care in carrying out the subspace iterations. We demonstrate the parallel scalability of the DG-CheFSI approach in calculations of large-scale twodimensional graphene sheets and bulk three-dimensional lithium-ion electrolyte systems. In conclusion, employing 55 296 computational cores, the time per self-consistent field iteration for a sample of the bulk 3D electrolyte containing 8586 atoms is 90 s, and the time for a graphene sheet containing 11 520 atoms is 75 s.« less

A multidisciplinary approach to the development of low-cost high-performance lightwave networks

NASA Technical Reports Server (NTRS)

Maitan, Jacek; Harwit, Alex

1991-01-01

Our research focuses on high-speed distributed systems. We anticipate that our results will allow the fabrication of low-cost networks employing multi-gigabit-per-second data links for space and military applications. The recent development of high-speed low-cost photonic components and new generations of microprocessors creates an opportunity to develop advanced large-scale distributed information systems. These systems currently involve hundreds of thousands of nodes and are made up of components and communications links that may fail during operation. In order to realize these systems, research is needed into technologies that foster adaptability and scaleability. Self-organizing mechanisms are needed to integrate a working fabric of large-scale distributed systems. The challenge is to fuse theory, technology, and development methodologies to construct a cost-effective, efficient, large-scale system.

Challenges and Opportunities: One Stop Processing of Automatic Large-Scale Base Map Production Using Airborne LIDAR Data Within GIS Environment. Case Study: Makassar City, Indonesia

NASA Astrophysics Data System (ADS)

Widyaningrum, E.; Gorte, B. G. H.

2017-05-01

LiDAR data acquisition is recognized as one of the fastest solutions to provide basis data for large-scale topographical base maps worldwide. Automatic LiDAR processing is believed one possible scheme to accelerate the large-scale topographic base map provision by the Geospatial Information Agency in Indonesia. As a progressive advanced technology, Geographic Information System (GIS) open possibilities to deal with geospatial data automatic processing and analyses. Considering further needs of spatial data sharing and integration, the one stop processing of LiDAR data in a GIS environment is considered a powerful and efficient approach for the base map provision. The quality of the automated topographic base map is assessed and analysed based on its completeness, correctness, quality, and the confusion matrix.

Visual attention mitigates information loss in small- and large-scale neural codes.

PubMed

Sprague, Thomas C; Saproo, Sameer; Serences, John T

2015-04-01

The visual system transforms complex inputs into robust and parsimonious neural codes that efficiently guide behavior. Because neural communication is stochastic, the amount of encoded visual information necessarily decreases with each synapse. This constraint requires that sensory signals are processed in a manner that protects information about relevant stimuli from degradation. Such selective processing--or selective attention--is implemented via several mechanisms, including neural gain and changes in tuning properties. However, examining each of these effects in isolation obscures their joint impact on the fidelity of stimulus feature representations by large-scale population codes. Instead, large-scale activity patterns can be used to reconstruct representations of relevant and irrelevant stimuli, thereby providing a holistic understanding about how neuron-level modulations collectively impact stimulus encoding. Copyright © 2015 Elsevier Ltd. All rights reserved.

The effect of environmental factors on technical and scale efficiency of primary health care providers in Greece.

PubMed

Kontodimopoulos, Nick; Moschovakis, Giorgos; Aletras, Vassilis H; Niakas, Dimitris

2007-11-17

The purpose of this study was to compare technical and scale efficiency of primary care centers from the two largest Greek providers, the National Health System (NHS) and the Social Security Foundation (IKA) and to determine if, and how, efficiency is affected by various exogenous factors such as catchment population and location. The sample comprised of 194 units (103 NHS and 91 IKA). Efficiency was measured with Data Envelopment Analysis (DEA) using three inputs, -medical staff, nursing/paramedical staff, administrative/other staff- and two outputs, which were the aggregated numbers of scheduled/emergency patient visits and imaging/laboratory diagnostic tests. Facilities were categorized as small, medium and large (<15,000, 15,000-30,000 and >30,000 respectively) to reflect catchment population and as urban/semi-urban or remote/island to reflect location. In a second stage analysis, technical and scale efficiency scores were regressed against facility type (NHS or IKA), size and location using multivariate Tobit regression. Regarding technical efficiency, IKA performed better than the NHS (84.9% vs. 70.1%, Mann-Whitney P < 0.001), smaller units better than medium-sized and larger ones (84.2% vs. 72.4% vs. 74.3%, Kruskal-Wallis P < 0.01) and remote/island units better than urban centers (81.1% vs. 75.7%, Mann-Whitney P = 0.103). As for scale efficiency, IKA again outperformed the NHS (89.7% vs. 85.9%, Mann-Whitney P = 0.080), but results were reversed in respect to facility size and location. Specifically, larger units performed better (96.3% vs. 90.9% vs. 75.9%, Kruskal-Wallis P < 0.001), and urban units showed higher scale efficiency than remote ones (91.9% vs. 75.3%, Mann-Whitney P < 0.001). Interestingly 75% of facilities appeared to be functioning under increasing returns to scale. Within-group comparisons revealed significant efficiency differences between the two primary care providers. Tobit regression models showed that facility type, size and location were significant explanatory variables of technical and scale efficiency. Variations appeared to exist in the productive performance of the NHS and IKA as the two main primary care providers in Greece. These variations reflect differences in primary care organization, economical incentives, financial constraints, sociodemographic and local peculiarities. In all technical efficiency comparisons, IKA facilities appeared to outperform NHS ones irrespective of facility size or location. In respect to scale efficiency, the results were to some extent inconclusive and observed differences were mostly insignificant, although again IKA appeared to perform better.

Demonstration of Hadoop-GIS: A Spatial Data Warehousing System Over MapReduce

PubMed Central

Aji, Ablimit; Sun, Xiling; Vo, Hoang; Liu, Qioaling; Lee, Rubao; Zhang, Xiaodong; Saltz, Joel; Wang, Fusheng

2016-01-01

The proliferation of GPS-enabled devices, and the rapid improvement of scientific instruments have resulted in massive amounts of spatial data in the last decade. Support of high performance spatial queries on large volumes data has become increasingly important in numerous fields, which requires a scalable and efficient spatial data warehousing solution as existing approaches exhibit scalability limitations and efficiency bottlenecks for large scale spatial applications. In this demonstration, we present Hadoop-GIS – a scalable and high performance spatial query system over MapReduce. Hadoop-GIS provides an efficient spatial query engine to process spatial queries, data and space based partitioning, and query pipelines that parallelize queries implicitly on MapReduce. Hadoop-GIS also provides an expressive, SQL-like spatial query language for workload specification. We will demonstrate how spatial queries are expressed in spatially extended SQL queries, and submitted through a command line/web interface for execution. Parallel to our system demonstration, we explain the system architecture and details on how queries are translated to MapReduce operators, optimized, and executed on Hadoop. In addition, we will showcase how the system can be used to support two representative real world use cases: large scale pathology analytical imaging, and geo-spatial data warehousing. PMID:27617325

Effectively Transparent Front Contacts for Optoelectronic Devices

DOE PAGES

Saive, Rebecca; Borsuk, Aleca M.; Emmer, Hal S.; ...

2016-06-10

Effectively transparent front contacts for optoelectronic devices achieve a measured transparency of up to 99.9% and a measured sheet resistance of 4.8 Ω sq-1. These 3D microscale triangular cross-section grid fingers redirect incoming photons efficiently to the active semiconductor area and can replace standard grid fingers as well as transparent conductive oxide layers in optoelectronic devices. Optoelectronic devices such as light emitting diodes, photodiodes, and solar cells play an important and expanding role in modern technology. Photovoltaics is one of the largest optoelectronic industry sectors and an ever-increasing component of the world's rapidly growing renewable carbon-free electricity generation infrastructure. Inmore » recent years, the photovoltaics field has dramatically expanded owing to the large-scale manufacture of inexpensive crystalline Si and thin film cells and modules. The current record efficiency (η = 25.6%) Si solar cell utilizes a heterostructure intrinsic thin layer (HIT) design[1] to enable increased open circuit voltage, while more mass-manufacturable solar cell architectures feature front contacts.[2, 3] Thus improved solar cell front contact designs are important for future large-scale photovoltaics with even higher efficiency.« less

Quench protection challenges in long nb3sn accelerator magnets

NASA Astrophysics Data System (ADS)

Salmi, Tiina-Mari; Ambrosio, G.; Caspi, S.; Chlachidze, Guram; Dhallé, Marc; Felice, Helene; Ferracin, Paolo; Marchevsky, M.; Sabbi, G. L.; ten Kate, H. H. J.

2012-06-01

The quench protection of the several meter long, large aperture high-field Nb3Sn quadrupoles that the LARP collaboration is developing for the LHC interaction region upgrade, requires efficient protection heaters to quickly generate large resistive segments across the windings. To support the protection design, experiments in the recently tested LARP R&D magnets are aimed to characterize the coil response to different protection schemes. In particular, the delay to quench and the final hotspot temperatures are evaluated after firing the heaters at different powering regimes and coverage. Also, the contribution of external energy extraction is investigated. Based on the performed studies and computer simulations, it seems that if the same protection efficiency per unit length that is measured in a 1 m long model magnet can be scaled to a 3.6 m long magnet, and the heater coverage can be improved, about 1 MJ/m of stored energy can be absorbed in the magnet after a quench. However, significant technology developments are needed to scale the protection heater efficiency to longer magnets and to increase the coverage.

PLUM: Parallel Load Balancing for Unstructured Adaptive Meshes. Degree awarded by Colorado Univ.

NASA Technical Reports Server (NTRS)

Oliker, Leonid

1998-01-01

Dynamic mesh adaption on unstructured grids is a powerful tool for computing large-scale problems that require grid modifications to efficiently resolve solution features. By locally refining and coarsening the mesh to capture physical phenomena of interest, such procedures make standard computational methods more cost effective. Unfortunately, an efficient parallel implementation of these adaptive methods is rather difficult to achieve, primarily due to the load imbalance created by the dynamically-changing nonuniform grid. This requires significant communication at runtime, leading to idle processors and adversely affecting the total execution time. Nonetheless, it is generally thought that unstructured adaptive- grid techniques will constitute a significant fraction of future high-performance supercomputing. Various dynamic load balancing methods have been reported to date; however, most of them either lack a global view of loads across processors or do not apply their techniques to realistic large-scale applications.

Efficient Power Network Analysis with Modeling of Inductive Effects

NASA Astrophysics Data System (ADS)

Zeng, Shan; Yu, Wenjian; Hong, Xianlong; Cheng, Chung-Kuan

In this paper, an efficient method is proposed to accurately analyze large-scale power/ground (P/G) networks, where inductive parasitics are modeled with the partial reluctance. The method is based on frequency-domain circuit analysis and the technique of vector fitting [14], and obtains the time-domain voltage response at given P/G nodes. The frequency-domain circuit equation including partial reluctances is derived, and then solved with the GMRES algorithm with rescaling, preconditioning and recycling techniques. With the merit of sparsified reluctance matrix and iterative solving techniques for the frequency-domain circuit equations, the proposed method is able to handle large-scale P/G networks with complete inductive modeling. Numerical results show that the proposed method is orders of magnitude faster than HSPICE, several times faster than INDUCTWISE [4], and capable of handling the inductive P/G structures with more than 100, 000 wire segments.

Iron-Air Rechargeable Battery: A Robust and Inexpensive Iron-Air Rechargeable Battery for Grid-Scale Energy Storage

DOE Office of Scientific and Technical Information (OSTI.GOV)

None

2010-10-01

GRIDS Project: USC is developing an iron-air rechargeable battery for large-scale energy storage that could help integrate renewable energy sources into the electric grid. Iron-air batteries have the potential to store large amounts of energy at low cost—iron is inexpensive and abundant, while oxygen is freely obtained from the air we breathe. However, current iron-air battery technologies have suffered from low efficiency and short life spans. USC is working to dramatically increase the efficiency of the battery by placing chemical additives on the battery’s iron-based electrode and restructuring the catalysts at the molecular level on the battery’s air-based electrode. Thismore » can help the battery resist degradation and increase life span. The goal of the project is to develop a prototype iron-air battery at significantly cost lower than today’s best commercial batteries.« less

Seismic data restoration with a fast L1 norm trust region method

NASA Astrophysics Data System (ADS)

Cao, Jingjie; Wang, Yanfei

2014-08-01

Seismic data restoration is a major strategy to provide reliable wavefield when field data dissatisfy the Shannon sampling theorem. Recovery by sparsity-promoting inversion often get sparse solutions of seismic data in a transformed domains, however, most methods for sparsity-promoting inversion are line-searching methods which are efficient but are inclined to obtain local solutions. Using trust region method which can provide globally convergent solutions is a good choice to overcome this shortcoming. A trust region method for sparse inversion has been proposed, however, the efficiency should be improved to suitable for large-scale computation. In this paper, a new L1 norm trust region model is proposed for seismic data restoration and a robust gradient projection method for solving the sub-problem is utilized. Numerical results of synthetic and field data demonstrate that the proposed trust region method can get excellent computation speed and is a viable alternative for large-scale computation.

Enrichment and separation techniques for large-scale proteomics analysis of the protein post-translational modifications.

PubMed

Huang, Junfeng; Wang, Fangjun; Ye, Mingliang; Zou, Hanfa

2014-11-06

Comprehensive analysis of the post-translational modifications (PTMs) on proteins at proteome level is crucial to elucidate the regulatory mechanisms of various biological processes. In the past decades, thanks to the development of specific PTM enrichment techniques and efficient multidimensional liquid chromatography (LC) separation strategy, the identification of protein PTMs have made tremendous progress. A huge number of modification sites for some major protein PTMs have been identified by proteomics analysis. In this review, we first introduced the recent progresses of PTM enrichment methods for the analysis of several major PTMs including phosphorylation, glycosylation, ubiquitination, acetylation, methylation, and oxidation/reduction status. We then briefly summarized the challenges for PTM enrichment. Finally, we introduced the fractionation and separation techniques for efficient separation of PTM peptides in large-scale PTM analysis. Copyright © 2014 Elsevier B.V. All rights reserved.

A numerical formulation and algorithm for limit and shakedown analysis of large-scale elastoplastic structures

NASA Astrophysics Data System (ADS)

Peng, Heng; Liu, Yinghua; Chen, Haofeng

2018-05-01

In this paper, a novel direct method called the stress compensation method (SCM) is proposed for limit and shakedown analysis of large-scale elastoplastic structures. Without needing to solve the specific mathematical programming problem, the SCM is a two-level iterative procedure based on a sequence of linear elastic finite element solutions where the global stiffness matrix is decomposed only once. In the inner loop, the static admissible residual stress field for shakedown analysis is constructed. In the outer loop, a series of decreasing load multipliers are updated to approach to the shakedown limit multiplier by using an efficient and robust iteration control technique, where the static shakedown theorem is adopted. Three numerical examples up to about 140,000 finite element nodes confirm the applicability and efficiency of this method for two-dimensional and three-dimensional elastoplastic structures, with detailed discussions on the convergence and the accuracy of the proposed algorithm.

Scalable methodology for large scale building energy improvement: Relevance of calibration in model-based retrofit analysis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Heo, Yeonsook; Augenbroe, Godfried; Graziano, Diane

2015-05-01

The increasing interest in retrofitting of existing buildings is motivated by the need to make a major contribution to enhancing building energy efficiency and reducing energy consumption and CO2 emission by the built environment. This paper examines the relevance of calibration in model-based analysis to support decision-making for energy and carbon efficiency retrofits of individual buildings and portfolios of buildings. The authors formulate a set of real retrofit decision-making situations and evaluate the role of calibration by using a case study that compares predictions and decisions from an uncalibrated model with those of a calibrated model. The case study illustratesmore » both the mechanics and outcomes of a practical alternative to the expert- and time-intense application of dynamic energy simulation models for large-scale retrofit decision-making under uncertainty.« less

Application of Large-Scale Database-Based Online Modeling to Plant State Long-Term Estimation

NASA Astrophysics Data System (ADS)

Ogawa, Masatoshi; Ogai, Harutoshi

Recently, attention has been drawn to the local modeling techniques of a new idea called “Just-In-Time (JIT) modeling”. To apply “JIT modeling” to a large amount of database online, “Large-scale database-based Online Modeling (LOM)” has been proposed. LOM is a technique that makes the retrieval of neighboring data more efficient by using both “stepwise selection” and quantization. In order to predict the long-term state of the plant without using future data of manipulated variables, an Extended Sequential Prediction method of LOM (ESP-LOM) has been proposed. In this paper, the LOM and the ESP-LOM are introduced.

A High-Performance Sintered Iron Electrode for Rechargeable Alkaline Batteries to Enable Large-Scale Energy Storage

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yang, Chenguang; Manohar, Aswin K.; Narayanan, S. R.

Iron-based alkaline rechargeable batteries such as iron-air and nickel-iron batteries are particularly attractive for large-scale energy storage because these batteries can be relatively inexpensive, environment- friendly, and also safe. Therefore, our study has focused on achieving the essential electrical performance and cycling properties needed for the widespread use of iron-based alkaline batteries in stationary and distributed energy storage applications.We have demonstrated for the first time, an advanced sintered iron electrode capable of 3500 cycles of repeated charge and discharge at the 1-hour rate and 100% depth of discharge in each cycle, and an average Coulombic efficiency of over 97%. Suchmore » a robust and efficient rechargeable iron electrode is also capable of continuous discharge at rates as high as 3C with no noticeable loss in utilization. We have shown that the porosity, pore size and thickness of the sintered electrode can be selected rationally to optimize specific capacity, rate capability and robustness. As a result, these advances in the electrical performance and durability of the iron electrode enables iron-based alkaline batteries to be a viable technology solution for meeting the dire need for large-scale electrical energy storage.« less

Registration of Aerial Optical Images with LiDAR Data Using the Closest Point Principle and Collinearity Equations.

PubMed

Huang, Rongyong; Zheng, Shunyi; Hu, Kun

2018-06-01

Registration of large-scale optical images with airborne LiDAR data is the basis of the integration of photogrammetry and LiDAR. However, geometric misalignments still exist between some aerial optical images and airborne LiDAR point clouds. To eliminate such misalignments, we extended a method for registering close-range optical images with terrestrial LiDAR data to a variety of large-scale aerial optical images and airborne LiDAR data. The fundamental principle is to minimize the distances from the photogrammetric matching points to the terrestrial LiDAR data surface. Except for the satisfactory efficiency of about 79 s per 6732 × 8984 image, the experimental results also show that the unit weighted root mean square (RMS) of the image points is able to reach a sub-pixel level (0.45 to 0.62 pixel), and the actual horizontal and vertical accuracy can be greatly improved to a high level of 1/4⁻1/2 (0.17⁻0.27 m) and 1/8⁻1/4 (0.10⁻0.15 m) of the average LiDAR point distance respectively. Finally, the method is proved to be more accurate, feasible, efficient, and practical in variety of large-scale aerial optical image and LiDAR data.

A High-Performance Sintered Iron Electrode for Rechargeable Alkaline Batteries to Enable Large-Scale Energy Storage

DOE PAGES

Yang, Chenguang; Manohar, Aswin K.; Narayanan, S. R.

2017-01-07

Iron-based alkaline rechargeable batteries such as iron-air and nickel-iron batteries are particularly attractive for large-scale energy storage because these batteries can be relatively inexpensive, environment- friendly, and also safe. Therefore, our study has focused on achieving the essential electrical performance and cycling properties needed for the widespread use of iron-based alkaline batteries in stationary and distributed energy storage applications.We have demonstrated for the first time, an advanced sintered iron electrode capable of 3500 cycles of repeated charge and discharge at the 1-hour rate and 100% depth of discharge in each cycle, and an average Coulombic efficiency of over 97%. Suchmore » a robust and efficient rechargeable iron electrode is also capable of continuous discharge at rates as high as 3C with no noticeable loss in utilization. We have shown that the porosity, pore size and thickness of the sintered electrode can be selected rationally to optimize specific capacity, rate capability and robustness. As a result, these advances in the electrical performance and durability of the iron electrode enables iron-based alkaline batteries to be a viable technology solution for meeting the dire need for large-scale electrical energy storage.« less

Dynamic displacement measurement of large-scale structures based on the Lucas-Kanade template tracking algorithm

NASA Astrophysics Data System (ADS)

Guo, Jie; Zhu, Chang`an

2016-01-01

The development of optics and computer technologies enables the application of the vision-based technique that uses digital cameras to the displacement measurement of large-scale structures. Compared with traditional contact measurements, vision-based technique allows for remote measurement, has a non-intrusive characteristic, and does not necessitate mass introduction. In this study, a high-speed camera system is developed to complete the displacement measurement in real time. The system consists of a high-speed camera and a notebook computer. The high-speed camera can capture images at a speed of hundreds of frames per second. To process the captured images in computer, the Lucas-Kanade template tracking algorithm in the field of computer vision is introduced. Additionally, a modified inverse compositional algorithm is proposed to reduce the computing time of the original algorithm and improve the efficiency further. The modified algorithm can rapidly accomplish one displacement extraction within 1 ms without having to install any pre-designed target panel onto the structures in advance. The accuracy and the efficiency of the system in the remote measurement of dynamic displacement are demonstrated in the experiments on motion platform and sound barrier on suspension viaduct. Experimental results show that the proposed algorithm can extract accurate displacement signal and accomplish the vibration measurement of large-scale structures.

An efficient and scalable analysis framework for variant extraction and refinement from population-scale DNA sequence data.

PubMed

Jun, Goo; Wing, Mary Kate; Abecasis, Gonçalo R; Kang, Hyun Min

2015-06-01

The analysis of next-generation sequencing data is computationally and statistically challenging because of the massive volume of data and imperfect data quality. We present GotCloud, a pipeline for efficiently detecting and genotyping high-quality variants from large-scale sequencing data. GotCloud automates sequence alignment, sample-level quality control, variant calling, filtering of likely artifacts using machine-learning techniques, and genotype refinement using haplotype information. The pipeline can process thousands of samples in parallel and requires less computational resources than current alternatives. Experiments with whole-genome and exome-targeted sequence data generated by the 1000 Genomes Project show that the pipeline provides effective filtering against false positive variants and high power to detect true variants. Our pipeline has already contributed to variant detection and genotyping in several large-scale sequencing projects, including the 1000 Genomes Project and the NHLBI Exome Sequencing Project. We hope it will now prove useful to many medical sequencing studies. © 2015 Jun et al.; Published by Cold Spring Harbor Laboratory Press.

Performance of fully-coupled algebraic multigrid preconditioners for large-scale VMS resistive MHD

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lin, P. T.; Shadid, J. N.; Hu, J. J.

Here, we explore the current performance and scaling of a fully-implicit stabilized unstructured finite element (FE) variational multiscale (VMS) capability for large-scale simulations of 3D incompressible resistive magnetohydrodynamics (MHD). The large-scale linear systems that are generated by a Newton nonlinear solver approach are iteratively solved by preconditioned Krylov subspace methods. The efficiency of this approach is critically dependent on the scalability and performance of the algebraic multigrid preconditioner. Our study considers the performance of the numerical methods as recently implemented in the second-generation Trilinos implementation that is 64-bit compliant and is not limited by the 32-bit global identifiers of themore » original Epetra-based Trilinos. The study presents representative results for a Poisson problem on 1.6 million cores of an IBM Blue Gene/Q platform to demonstrate very large-scale parallel execution. Additionally, results for a more challenging steady-state MHD generator and a transient solution of a benchmark MHD turbulence calculation for the full resistive MHD system are also presented. These results are obtained on up to 131,000 cores of a Cray XC40 and one million cores of a BG/Q system.« less

Performance of fully-coupled algebraic multigrid preconditioners for large-scale VMS resistive MHD

DOE PAGES

Lin, P. T.; Shadid, J. N.; Hu, J. J.; ...

2017-11-06

Here, we explore the current performance and scaling of a fully-implicit stabilized unstructured finite element (FE) variational multiscale (VMS) capability for large-scale simulations of 3D incompressible resistive magnetohydrodynamics (MHD). The large-scale linear systems that are generated by a Newton nonlinear solver approach are iteratively solved by preconditioned Krylov subspace methods. The efficiency of this approach is critically dependent on the scalability and performance of the algebraic multigrid preconditioner. Our study considers the performance of the numerical methods as recently implemented in the second-generation Trilinos implementation that is 64-bit compliant and is not limited by the 32-bit global identifiers of themore » original Epetra-based Trilinos. The study presents representative results for a Poisson problem on 1.6 million cores of an IBM Blue Gene/Q platform to demonstrate very large-scale parallel execution. Additionally, results for a more challenging steady-state MHD generator and a transient solution of a benchmark MHD turbulence calculation for the full resistive MHD system are also presented. These results are obtained on up to 131,000 cores of a Cray XC40 and one million cores of a BG/Q system.« less

Comparing centralised and decentralised anaerobic digestion of stillage from a large-scale bioethanol plant to animal feed production.

PubMed

Drosg, B; Wirthensohn, T; Konrad, G; Hornbachner, D; Resch, C; Wäger, F; Loderer, C; Waltenberger, R; Kirchmayr, R; Braun, R

2008-01-01

A comparison of stillage treatment options for large-scale bioethanol plants was based on the data of an existing plant producing approximately 200,000 t/yr of bioethanol and 1,400,000 t/yr of stillage. Animal feed production--the state-of-the-art technology at the plant--was compared to anaerobic digestion. The latter was simulated in two different scenarios: digestion in small-scale biogas plants in the surrounding area versus digestion in a large-scale biogas plant at the bioethanol production site. Emphasis was placed on a holistic simulation balancing chemical parameters and calculating logistic algorithms to compare the efficiency of the stillage treatment solutions. For central anaerobic digestion different digestate handling solutions were considered because of the large amount of digestate. For land application a minimum of 36,000 ha of available agricultural area would be needed and 600,000 m(3) of storage volume. Secondly membrane purification of the digestate was investigated consisting of decanter, microfiltration, and reverse osmosis. As a third option aerobic wastewater treatment of the digestate was discussed. The final outcome was an economic evaluation of the three mentioned stillage treatment options, as a guide to stillage management for operators of large-scale bioethanol plants. Copyright IWA Publishing 2008.

The photobiological production of hydrogen: potential efficiency and effectiveness as a renewable fuel.

PubMed

Prince, Roger C; Kheshgi, Haroon S

2005-01-01

Photosynthetic microorganisms can produce hydrogen when illuminated, and there has been considerable interest in developing this to a commercially viable process. Its appealing aspects include the fact that the hydrogen would come from water, and that the process might be more energetically efficient than growing, harvesting, and processing crops. We review current knowledge about photobiological hydrogen production, and identify and discuss some of the areas where scientific and technical breakthroughs are essential for commercialization. First we describe the underlying biochemistry of the process, and identify some opportunities for improving photobiological hydrogen production at the molecular level. Then we address the fundamental quantum efficiency of the various processes that have been suggested, technological issues surrounding large-scale growth of hydrogen-producing microorganisms, and the scale and efficiency on which this would have to be practiced to make a significant contribution to current energy use.

Drag and Propulsive Characteristics of Air-Cooled Engine-Nacelle Installations for Large Airplane

NASA Technical Reports Server (NTRS)

Silverstein, Abe; Wilson, Herbert A , Jr

1942-01-01

An investigation was conducted in the NACA full-scale wind tunnel to determine the drag and the propulsive efficiency of nacelle-propeller arrangements for a large range of nacelle sizes. In contrast with usual tests with a single nacelle, these tests were conducted with nacelle-propeller installations on a large model of a four-engine airplane. Data are presented on the first part of the investigation, covering seven nacelle arrangements with nacelle diameters from 0.53 to 1.5 times the wing thickness. These ratios are similar to those occurring on airplanes weighing from about 20 to 100 tons. The results show the drag, the propulsive efficiency, and the over-all efficiency of the various nacelle arrangements as functions of the nacelle size, the propeller position, and the airplane lift coefficient. The effect of the nacelles on the aerodynamic characteristics of the model is shown for both propeller-removed and propeller-operating conditions.

HIGH-EFFICIENCY AUTONOMOUS LASER ADAPTIVE OPTICS

DOE Office of Scientific and Technical Information (OSTI.GOV)

Baranec, Christoph; Riddle, Reed; Tendulkar, Shriharsh

2014-07-20

As new large-scale astronomical surveys greatly increase the number of objects targeted and discoveries made, the requirement for efficient follow-up observations is crucial. Adaptive optics imaging, which compensates for the image-blurring effects of Earth's turbulent atmosphere, is essential for these surveys, but the scarcity, complexity and high demand of current systems limit their availability for following up large numbers of targets. To address this need, we have engineered and implemented Robo-AO, a fully autonomous laser adaptive optics and imaging system that routinely images over 200 objects per night with an acuity 10 times sharper at visible wavelengths than typically possible frommore » the ground. By greatly improving the angular resolution, sensitivity, and efficiency of 1-3 m class telescopes, we have eliminated a major obstacle in the follow-up of the discoveries from current and future large astronomical surveys.« less

A Parallel Sliding Region Algorithm to Make Agent-Based Modeling Possible for a Large-Scale Simulation: Modeling Hepatitis C Epidemics in Canada.

PubMed

Wong, William W L; Feng, Zeny Z; Thein, Hla-Hla

2016-11-01

Agent-based models (ABMs) are computer simulation models that define interactions among agents and simulate emergent behaviors that arise from the ensemble of local decisions. ABMs have been increasingly used to examine trends in infectious disease epidemiology. However, the main limitation of ABMs is the high computational cost for a large-scale simulation. To improve the computational efficiency for large-scale ABM simulations, we built a parallelizable sliding region algorithm (SRA) for ABM and compared it to a nonparallelizable ABM. We developed a complex agent network and performed two simulations to model hepatitis C epidemics based on the real demographic data from Saskatchewan, Canada. The first simulation used the SRA that processed on each postal code subregion subsequently. The second simulation processed the entire population simultaneously. It was concluded that the parallelizable SRA showed computational time saving with comparable results in a province-wide simulation. Using the same method, SRA can be generalized for performing a country-wide simulation. Thus, this parallel algorithm enables the possibility of using ABM for large-scale simulation with limited computational resources.

A Combined Eulerian-Lagrangian Data Representation for Large-Scale Applications.

PubMed

Sauer, Franz; Xie, Jinrong; Ma, Kwan-Liu

2017-10-01

The Eulerian and Lagrangian reference frames each provide a unique perspective when studying and visualizing results from scientific systems. As a result, many large-scale simulations produce data in both formats, and analysis tasks that simultaneously utilize information from both representations are becoming increasingly popular. However, due to their fundamentally different nature, drawing correlations between these data formats is a computationally difficult task, especially in a large-scale setting. In this work, we present a new data representation which combines both reference frames into a joint Eulerian-Lagrangian format. By reorganizing Lagrangian information according to the Eulerian simulation grid into a "unit cell" based approach, we can provide an efficient out-of-core means of sampling, querying, and operating with both representations simultaneously. We also extend this design to generate multi-resolution subsets of the full data to suit the viewer's needs and provide a fast flow-aware trajectory construction scheme. We demonstrate the effectiveness of our method using three large-scale real world scientific datasets and provide insight into the types of performance gains that can be achieved.

Communication: A reduced scaling J-engine based reformulation of SOS-MP2 using graphics processing units

DOE Office of Scientific and Technical Information (OSTI.GOV)

Maurer, S. A.; Kussmann, J.; Ochsenfeld, C., E-mail: Christian.Ochsenfeld@cup.uni-muenchen.de

2014-08-07

We present a low-prefactor, cubically scaling scaled-opposite-spin second-order Møller-Plesset perturbation theory (SOS-MP2) method which is highly suitable for massively parallel architectures like graphics processing units (GPU). The scaling is reduced from O(N{sup 5}) to O(N{sup 3}) by a reformulation of the MP2-expression in the atomic orbital basis via Laplace transformation and the resolution-of-the-identity (RI) approximation of the integrals in combination with efficient sparse algebra for the 3-center integral transformation. In contrast to previous works that employ GPUs for post Hartree-Fock calculations, we do not simply employ GPU-based linear algebra libraries to accelerate the conventional algorithm. Instead, our reformulation allows tomore » replace the rate-determining contraction step with a modified J-engine algorithm, that has been proven to be highly efficient on GPUs. Thus, our SOS-MP2 scheme enables us to treat large molecular systems in an accurate and efficient manner on a single GPU-server.« less

Large temporal scale and capacity subsurface bulk energy storage with CO2

NASA Astrophysics Data System (ADS)

Saar, M. O.; Fleming, M. R.; Adams, B. M.; Ogland-Hand, J.; Nelson, E. S.; Randolph, J.; Sioshansi, R.; Kuehn, T. H.; Buscheck, T. A.; Bielicki, J. M.

2017-12-01

Decarbonizing energy systems by increasing the penetration of variable renewable energy (VRE) technologies requires efficient and short- to long-term energy storage. Very large amounts of energy can be stored in the subsurface as heat and/or pressure energy in order to provide both short- and long-term (seasonal) storage, depending on the implementation. This energy storage approach can be quite efficient, especially where geothermal energy is naturally added to the system. Here, we present subsurface heat and/or pressure energy storage with supercritical carbon dioxide (CO2) and discuss the system's efficiency, deployment options, as well as its advantages and disadvantages, compared to several other energy storage options. CO2-based subsurface bulk energy storage has the potential to be particularly efficient and large-scale, both temporally (i.e., seasonal) and spatially. The latter refers to the amount of energy that can be stored underground, using CO2, at a geologically conducive location, potentially enabling storing excess power from a substantial portion of the power grid. The implication is that it would be possible to employ centralized energy storage for (a substantial part of) the power grid, where the geology enables CO2-based bulk subsurface energy storage, whereas the VRE technologies (solar, wind) are located on that same power grid, where (solar, wind) conditions are ideal. However, this may require reinforcing the power grid's transmission lines in certain parts of the grid to enable high-load power transmission from/to a few locations.

On the Large-Scaling Issues of Cloud-based Applications for Earth Science Dat

NASA Astrophysics Data System (ADS)

Hua, H.

2016-12-01

Next generation science data systems are needed to address the incoming flood of data from new missions such as NASA's SWOT and NISAR where its SAR data volumes and data throughput rates are order of magnitude larger than present day missions. Existing missions, such as OCO-2, may also require high turn-around time for processing different science scenarios where on-premise and even traditional HPC computing environments may not meet the high processing needs. Additionally, traditional means of procuring hardware on-premise are already limited due to facilities capacity constraints for these new missions. Experiences have shown that to embrace efficient cloud computing approaches for large-scale science data systems requires more than just moving existing code to cloud environments. At large cloud scales, we need to deal with scaling and cost issues. We present our experiences on deploying multiple instances of our hybrid-cloud computing science data system (HySDS) to support large-scale processing of Earth Science data products. We will explore optimization approaches to getting best performance out of hybrid-cloud computing as well as common issues that will arise when dealing with large-scale computing. Novel approaches were utilized to do processing on Amazon's spot market, which can potentially offer 75%-90% costs savings but with an unpredictable computing environment based on market forces.

Self Assembly and Pyroelectric Poling for Organics

DTIC Science & Technology

2015-07-06

ozone or nitrogen oxides) and energetic species from corona discharge . These problems can strongly inhibit the efficient poling and large-scale...poling techniques. Although contact and corona poling protocols are quite well established for decades, there do exist some challenging problems. In...contact poling, severe charge injection from metal electrodes often results in large current that causes dielectric breakdown of films. Corona poling

Comparing Human and Automated Essay Scoring for Prospective Graduate Students with Learning Disabilities and/or ADHD

ERIC Educational Resources Information Center

Buzick, Heather; Oliveri, Maria Elena; Attali, Yigal; Flor, Michael

2016-01-01

Automated essay scoring is a developing technology that can provide efficient scoring of large numbers of written responses. Its use in higher education admissions testing provides an opportunity to collect validity and fairness evidence to support current uses and inform its emergence in other areas such as K-12 large-scale assessment. In this…

Active Exploration of Large 3D Model Repositories.

PubMed

Gao, Lin; Cao, Yan-Pei; Lai, Yu-Kun; Huang, Hao-Zhi; Kobbelt, Leif; Hu, Shi-Min

2015-12-01

With broader availability of large-scale 3D model repositories, the need for efficient and effective exploration becomes more and more urgent. Existing model retrieval techniques do not scale well with the size of the database since often a large number of very similar objects are returned for a query, and the possibilities to refine the search are quite limited. We propose an interactive approach where the user feeds an active learning procedure by labeling either entire models or parts of them as "like" or "dislike" such that the system can automatically update an active set of recommended models. To provide an intuitive user interface, candidate models are presented based on their estimated relevance for the current query. From the methodological point of view, our main contribution is to exploit not only the similarity between a query and the database models but also the similarities among the database models themselves. We achieve this by an offline pre-processing stage, where global and local shape descriptors are computed for each model and a sparse distance metric is derived that can be evaluated efficiently even for very large databases. We demonstrate the effectiveness of our method by interactively exploring a repository containing over 100 K models.

Low-energy transmission electron diffraction and imaging of large-area graphene

PubMed Central

Zhao, Wei; Xia, Bingyu; Lin, Li; Xiao, Xiaoyang; Liu, Peng; Lin, Xiaoyang; Peng, Hailin; Zhu, Yuanmin; Yu, Rong; Lei, Peng; Wang, Jiangtao; Zhang, Lina; Xu, Yong; Zhao, Mingwen; Peng, Lianmao; Li, Qunqing; Duan, Wenhui; Liu, Zhongfan; Fan, Shoushan; Jiang, Kaili

2017-01-01

Two-dimensional (2D) materials have attracted interest because of their excellent properties and potential applications. A key step in realizing industrial applications is to synthesize wafer-scale single-crystal samples. Until now, single-crystal samples, such as graphene domains up to the centimeter scale, have been synthesized. However, a new challenge is to efficiently characterize large-area samples. Currently, the crystalline characterization of these samples still relies on selected-area electron diffraction (SAED) or low-energy electron diffraction (LEED), which is more suitable for characterizing very small local regions. This paper presents a highly efficient characterization technique that adopts a low-energy electrostatically focused electron gun and a super-aligned carbon nanotube (SACNT) film sample support. It allows rapid crystalline characterization of large-area graphene through a single photograph of a transmission-diffracted image at a large beam size. Additionally, the low-energy electron beam enables the observation of a unique diffraction pattern of adsorbates on the suspended graphene at room temperature. This work presents a simple and convenient method for characterizing the macroscopic structures of 2D materials, and the instrument we constructed allows the study of the weak interaction with 2D materials. PMID:28879233

Low-energy transmission electron diffraction and imaging of large-area graphene.

PubMed

Zhao, Wei; Xia, Bingyu; Lin, Li; Xiao, Xiaoyang; Liu, Peng; Lin, Xiaoyang; Peng, Hailin; Zhu, Yuanmin; Yu, Rong; Lei, Peng; Wang, Jiangtao; Zhang, Lina; Xu, Yong; Zhao, Mingwen; Peng, Lianmao; Li, Qunqing; Duan, Wenhui; Liu, Zhongfan; Fan, Shoushan; Jiang, Kaili

2017-09-01

Two-dimensional (2D) materials have attracted interest because of their excellent properties and potential applications. A key step in realizing industrial applications is to synthesize wafer-scale single-crystal samples. Until now, single-crystal samples, such as graphene domains up to the centimeter scale, have been synthesized. However, a new challenge is to efficiently characterize large-area samples. Currently, the crystalline characterization of these samples still relies on selected-area electron diffraction (SAED) or low-energy electron diffraction (LEED), which is more suitable for characterizing very small local regions. This paper presents a highly efficient characterization technique that adopts a low-energy electrostatically focused electron gun and a super-aligned carbon nanotube (SACNT) film sample support. It allows rapid crystalline characterization of large-area graphene through a single photograph of a transmission-diffracted image at a large beam size. Additionally, the low-energy electron beam enables the observation of a unique diffraction pattern of adsorbates on the suspended graphene at room temperature. This work presents a simple and convenient method for characterizing the macroscopic structures of 2D materials, and the instrument we constructed allows the study of the weak interaction with 2D materials.

Optimizing Cluster Heads for Energy Efficiency in Large-Scale Heterogeneous Wireless Sensor Networks

DOE PAGES

Gu, Yi; Wu, Qishi; Rao, Nageswara S. V.

2010-01-01

Many complex sensor network applications require deploying a large number of inexpensive and small sensors in a vast geographical region to achieve quality through quantity. Hierarchical clustering is generally considered as an efficient and scalable way to facilitate the management and operation of such large-scale networks and minimize the total energy consumption for prolonged lifetime. Judicious selection of cluster heads for data integration and communication is critical to the success of applications based on hierarchical sensor networks organized as layered clusters. We investigate the problem of selecting sensor nodes in a predeployed sensor network to be the cluster heads tomore » minimize the total energy needed for data gathering. We rigorously derive an analytical formula to optimize the number of cluster heads in sensor networks under uniform node distribution, and propose a Distance-based Crowdedness Clustering algorithm to determine the cluster heads in sensor networks under general node distribution. The results from an extensive set of experiments on a large number of simulated sensor networks illustrate the performance superiority of the proposed solution over the clustering schemes based on k -means algorithm.« less

Low-Temperature Soft-Cover Deposition of Uniform Large-Scale Perovskite Films for High-Performance Solar Cells.

PubMed

Ye, Fei; Tang, Wentao; Xie, Fengxian; Yin, Maoshu; He, Jinjin; Wang, Yanbo; Chen, Han; Qiang, Yinghuai; Yang, Xudong; Han, Liyuan

2017-09-01

Large-scale high-quality perovskite thin films are crucial to produce high-performance perovskite solar cells. However, for perovskite films fabricated by solvent-rich processes, film uniformity can be prevented by convection during thermal evaporation of the solvent. Here, a scalable low-temperature soft-cover deposition (LT-SCD) method is presented, where the thermal convection-induced defects in perovskite films are eliminated through a strategy of surface tension relaxation. Compact, homogeneous, and convection-induced-defects-free perovskite films are obtained on an area of 12 cm 2 , which enables a power conversion efficiency (PCE) of 15.5% on a solar cell with an area of 5 cm 2 . This is the highest efficiency at this large cell area. A PCE of 15.3% is also obtained on a flexible perovskite solar cell deposited on the polyethylene terephthalate substrate owing to the advantage of presented low-temperature processing. Hence, the present LT-SCD technology provides a new non-spin-coating route to the deposition of large-area uniform perovskite films for both rigid and flexible perovskite devices. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Scaling and criticality in a stochastic multi-agent model of a financial market

NASA Astrophysics Data System (ADS)

Lux, Thomas; Marchesi, Michele

1999-02-01

Financial prices have been found to exhibit some universal characteristics that resemble the scaling laws characterizing physical systems in which large numbers of units interact. This raises the question of whether scaling in finance emerges in a similar way - from the interactions of a large ensemble of market participants. However, such an explanation is in contradiction to the prevalent `efficient market hypothesis' in economics, which assumes that the movements of financial prices are an immediate and unbiased reflection of incoming news about future earning prospects. Within this hypothesis, scaling in price changes would simply reflect similar scaling in the `input' signals that influence them. Here we describe a multi-agent model of financial markets which supports the idea that scaling arises from mutual interactions of participants. Although the `news arrival process' in our model lacks both power-law scaling and any temporal dependence in volatility, we find that it generates such behaviour as a result of interactions between agents.

ELECTRON ACCELERATION AT A CORONAL SHOCK PROPAGATING THROUGH A LARGE-SCALE STREAMER-LIKE MAGNETIC FIELD

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kong, Xiangliang; Chen, Yao; Feng, Shiwei

2016-04-10

Using a test-particle simulation, we investigate the effect of large-scale coronal magnetic fields on electron acceleration at an outward-propagating coronal shock with a circular front. The coronal field is approximated by an analytical solution with a streamer-like magnetic field featuring a partially open magnetic field and a current sheet at the equator atop the closed region. We show that the large-scale shock-field configuration, especially the relative curvature of the shock and the magnetic field line across which the shock is sweeping, plays an important role in the efficiency of electron acceleration. At low shock altitudes, when the shock curvature ismore » larger than that of the magnetic field lines, the electrons are mainly accelerated at the shock flanks; at higher altitudes, when the shock curvature is smaller, the electrons are mainly accelerated at the shock nose around the top of closed field lines. The above process reveals the shift of the efficient electron acceleration region along the shock front during its propagation. We also find that, in general, the electron acceleration at the shock flank is not as efficient as that at the top of the closed field because a collapsing magnetic trap can be formed at the top. In addition, we find that the energy spectra of electrons are power-law-like, first hardening then softening with the spectral index varying in a range of −3 to −6. Physical interpretations of the results and implications for the study of solar radio bursts are discussed.« less

Jimena: efficient computing and system state identification for genetic regulatory networks.

PubMed

Karl, Stefan; Dandekar, Thomas

2013-10-11

Boolean networks capture switching behavior of many naturally occurring regulatory networks. For semi-quantitative modeling, interpolation between ON and OFF states is necessary. The high degree polynomial interpolation of Boolean genetic regulatory networks (GRNs) in cellular processes such as apoptosis or proliferation allows for the modeling of a wider range of node interactions than continuous activator-inhibitor models, but suffers from scaling problems for networks which contain nodes with more than ~10 inputs. Many GRNs from literature or new gene expression experiments exceed those limitations and a new approach was developed. (i) As a part of our new GRN simulation framework Jimena we introduce and setup Boolean-tree-based data structures; (ii) corresponding algorithms greatly expedite the calculation of the polynomial interpolation in almost all cases, thereby expanding the range of networks which can be simulated by this model in reasonable time. (iii) Stable states for discrete models are efficiently counted and identified using binary decision diagrams. As application example, we show how system states can now be sampled efficiently in small up to large scale hormone disease networks (Arabidopsis thaliana development and immunity, pathogen Pseudomonas syringae and modulation by cytokinins and plant hormones). Jimena simulates currently available GRNs about 10-100 times faster than the previous implementation of the polynomial interpolation model and even greater gains are achieved for large scale-free networks. This speed-up also facilitates a much more thorough sampling of continuous state spaces which may lead to the identification of new stable states. Mutants of large networks can be constructed and analyzed very quickly enabling new insights into network robustness and behavior.

Electron acceleration at a coronal shock propagating through a large-scale streamer-like magnetic field

DOE PAGES

Kong, Xiangliang; Chen, Yao; Guo, Fan; ...

2016-04-05

With a test-particle simulation, we investigate the effect of large-scale coronal magnetic fields on electron acceleration at an outward-propagating coronal shock with a circular front. The coronal field is approximated by an analytical solution with a streamer-like magnetic field featured by partially open magnetic field and a current sheet at the equator atop the closed region. We show that the large-scale shock-field configuration, especially the relative curvature of the shock and the magnetic field line across which the shock is sweeping, plays an important role in the efficiency of electron acceleration. At low shock altitudes, when the shock curvature ismore » larger than that of magnetic field lines, the electrons are mainly accelerated at the shock flanks; at higher altitudes, when the shock curvature is smaller, the electrons are mainly accelerated at the shock nose around the top of closed field lines. The above process reveals the shift of efficient electron acceleration region along the shock front during its propagation. We also found that in general the electron acceleration at the shock flank is not so efficient as that at the top of closed field since at the top a collapsing magnetic trap can be formed. In addition, we find that the energy spectra of electrons is power-law like, first hardening then softening with the spectral index varying in a range of -3 to -6. In conclusion, physical interpretations of the results and implications on the study of solar radio bursts are discussed.« less

Environmental performance evaluation of large-scale municipal solid waste incinerators using data envelopment analysis.

PubMed

Chen, Ho-Wen; Chang, Ni-Bin; Chen, Jeng-Chung; Tsai, Shu-Ju

2010-07-01

Limited to insufficient land resources, incinerators are considered in many countries such as Japan and Germany as the major technology for a waste management scheme capable of dealing with the increasing demand for municipal and industrial solid waste treatment in urban regions. The evaluation of these municipal incinerators in terms of secondary pollution potential, cost-effectiveness, and operational efficiency has become a new focus in the highly interdisciplinary area of production economics, systems analysis, and waste management. This paper aims to demonstrate the application of data envelopment analysis (DEA)--a production economics tool--to evaluate performance-based efficiencies of 19 large-scale municipal incinerators in Taiwan with different operational conditions. A 4-year operational data set from 2002 to 2005 was collected in support of DEA modeling using Monte Carlo simulation to outline the possibility distributions of operational efficiency of these incinerators. Uncertainty analysis using the Monte Carlo simulation provides a balance between simplifications of our analysis and the soundness of capturing the essential random features that complicate solid waste management systems. To cope with future challenges, efforts in the DEA modeling, systems analysis, and prediction of the performance of large-scale municipal solid waste incinerators under normal operation and special conditions were directed toward generating a compromised assessment procedure. Our research findings will eventually lead to the identification of the optimal management strategies for promoting the quality of solid waste incineration, not only in Taiwan, but also elsewhere in the world. Copyright (c) 2010 Elsevier Ltd. All rights reserved.

Efficiency and multifractality analysis of CSI 300 based on multifractal detrending moving average algorithm

NASA Astrophysics Data System (ADS)

Zhou, Weijie; Dang, Yaoguo; Gu, Rongbao

2013-03-01

We apply the multifractal detrending moving average (MFDMA) to investigate and compare the efficiency and multifractality of 5-min high-frequency China Securities Index 300 (CSI 300). The results show that the CSI 300 market becomes closer to weak-form efficiency after the introduction of CSI 300 future. We find that the CSI 300 is featured by multifractality and there are less complexity and risk after the CSI 300 index future was introduced. With the shuffling, surrogating and removing extreme values procedures, we unveil that extreme events and fat-distribution are the main origin of multifractality. Besides, we discuss the knotting phenomena in multifractality, and find that the scaling range and the irregular fluctuations for large scales in the Fq(s) vs s plot can cause a knot.

Asynchronous Two-Level Checkpointing Scheme for Large-Scale Adjoints in the Spectral-Element Solver Nek5000

DOE Office of Scientific and Technical Information (OSTI.GOV)

Schanen, Michel; Marin, Oana; Zhang, Hong

Adjoints are an important computational tool for large-scale sensitivity evaluation, uncertainty quantification, and derivative-based optimization. An essential component of their performance is the storage/recomputation balance in which efficient checkpointing methods play a key role. We introduce a novel asynchronous two-level adjoint checkpointing scheme for multistep numerical time discretizations targeted at large-scale numerical simulations. The checkpointing scheme combines bandwidth-limited disk checkpointing and binomial memory checkpointing. Based on assumptions about the target petascale systems, which we later demonstrate to be realistic on the IBM Blue Gene/Q system Mira, we create a model of the expected performance of our checkpointing approach and validatemore » it using the highly scalable Navier-Stokes spectralelement solver Nek5000 on small to moderate subsystems of the Mira supercomputer. In turn, this allows us to predict optimal algorithmic choices when using all of Mira. We also demonstrate that two-level checkpointing is significantly superior to single-level checkpointing when adjoining a large number of time integration steps. To our knowledge, this is the first time two-level checkpointing had been designed, implemented, tuned, and demonstrated on fluid dynamics codes at large scale of 50k+ cores.« less

Fluid-structure interaction simulation of floating structures interacting with complex, large-scale ocean waves and atmospheric turbulence with application to floating offshore wind turbines

NASA Astrophysics Data System (ADS)

Calderer, Antoni; Guo, Xin; Shen, Lian; Sotiropoulos, Fotis

2018-02-01

We develop a numerical method for simulating coupled interactions of complex floating structures with large-scale ocean waves and atmospheric turbulence. We employ an efficient large-scale model to develop offshore wind and wave environmental conditions, which are then incorporated into a high resolution two-phase flow solver with fluid-structure interaction (FSI). The large-scale wind-wave interaction model is based on a two-fluid dynamically-coupled approach that employs a high-order spectral method for simulating the water motion and a viscous solver with undulatory boundaries for the air motion. The two-phase flow FSI solver is based on the level set method and is capable of simulating the coupled dynamic interaction of arbitrarily complex bodies with airflow and waves. The large-scale wave field solver is coupled with the near-field FSI solver with a one-way coupling approach by feeding into the latter waves via a pressure-forcing method combined with the level set method. We validate the model for both simple wave trains and three-dimensional directional waves and compare the results with experimental and theoretical solutions. Finally, we demonstrate the capabilities of the new computational framework by carrying out large-eddy simulation of a floating offshore wind turbine interacting with realistic ocean wind and waves.

The Chandra Deep Wide-Field Survey: Completing the new generation of Chandra extragalactic surveys

NASA Astrophysics Data System (ADS)

Hickox, Ryan

2016-09-01

Chandra X-ray surveys have revolutionized our view of the growth of black holes across cosmic time. Recently, fundamental questions have emerged about the connection of AGN to their host large scale structures that clearly demand a wide, deep survey over a large area, comparable to the recent extensive Chandra surveys in smaller fields. We propose the Chandra Deep Wide-Field Survey (CDWFS) covering the central 6 sq. deg in the Bootes field, totaling 1.025 Ms (building on 550 ks from the HRC GTO program). CDWFS will efficiently probe a large cosmic volume, allowing us to carry out accurate new investigations of the connections between black holes and their large-scale structures, and will complete the next generation surveys that comprise a key part of Chandra's legacy.

Statewide mesoscopic simulation for Wyoming.

DOT National Transportation Integrated Search

2013-10-01

This study developed a mesoscopic simulator which is capable of representing both city-level and statewide roadway : networks. The key feature of such models are the integration of (i) a traffic flow model which is efficient enough to : scale to larg...

Large Scale Evaluation fo Nickel Aluminide Rolls

DOE Office of Scientific and Technical Information (OSTI.GOV)

None

2005-09-01

This completed project was a joint effort between Oak Ridge National Laboratory and Bethlehem Steel (now Mittal Steel) to demonstrate the effectiveness of using nickel aluminide intermetallic alloy rolls as part of an updated, energy-efficient, commercial annealing furnace system.

Generalized Master Equation with Non-Markovian Multichromophoric Förster Resonance Energy Transfer for Modular Exciton Densities

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jang, Seogjoo; Hoyer, Stephan; Fleming, Graham

2014-10-31

A generalized master equation (GME) governing quantum evolution of modular exciton density (MED) is derived for large scale light harvesting systems composed of weakly interacting modules of multiple chromophores. The GME-MED offers a practical framework to incorporate real time coherent quantum dynamics calculations of small length scales into dynamics over large length scales, and also provides a non-Markovian generalization and rigorous derivation of the Pauli master equation employing multichromophoric Förster resonance energy transfer rates. A test of the GME-MED for four sites of the Fenna-Matthews-Olson complex demonstrates how coherent dynamics of excitonic populations over coupled chromophores can be accurately describedmore » by transitions between subgroups (modules) of delocalized excitons. Application of the GME-MED to the exciton dynamics between a pair of light harvesting complexes in purple bacteria demonstrates its promise as a computationally efficient tool to investigate large scale exciton dynamics in complex environments.« less

Performance of Extended Local Clustering Organization (LCO) for Large Scale Job-Shop Scheduling Problem (JSP)

NASA Astrophysics Data System (ADS)

Konno, Yohko; Suzuki, Keiji

This paper describes an approach to development of a solution algorithm of a general-purpose for large scale problems using “Local Clustering Organization (LCO)” as a new solution for Job-shop scheduling problem (JSP). Using a performance effective large scale scheduling in the study of usual LCO, a solving JSP keep stability induced better solution is examined. In this study for an improvement of a performance of a solution for JSP, processes to a optimization by LCO is examined, and a scheduling solution-structure is extended to a new solution-structure based on machine-division. A solving method introduced into effective local clustering for the solution-structure is proposed as an extended LCO. An extended LCO has an algorithm which improves scheduling evaluation efficiently by clustering of parallel search which extends over plural machines. A result verified by an application of extended LCO on various scale of problems proved to conduce to minimizing make-span and improving on the stable performance.

Inter-annual and decadal changes in teleconnections drive continental-scale synchronization of tree reproduction.

PubMed

Ascoli, Davide; Vacchiano, Giorgio; Turco, Marco; Conedera, Marco; Drobyshev, Igor; Maringer, Janet; Motta, Renzo; Hacket-Pain, Andrew

2017-12-20

Climate teleconnections drive highly variable and synchronous seed production (masting) over large scales. Disentangling the effect of high-frequency (inter-annual variation) from low-frequency (decadal trends) components of climate oscillations will improve our understanding of masting as an ecosystem process. Using century-long observations on masting (the MASTREE database) and data on the Northern Atlantic Oscillation (NAO), we show that in the last 60 years both high-frequency summer and spring NAO, and low-frequency winter NAO components are highly correlated to continent-wide masting in European beech and Norway spruce. Relationships are weaker (non-stationary) in the early twentieth century. This finding improves our understanding on how climate variation affects large-scale synchronization of tree masting. Moreover, it supports the connection between proximate and ultimate causes of masting: indeed, large-scale features of atmospheric circulation coherently drive cues and resources for masting, as well as its evolutionary drivers, such as pollination efficiency, abundance of seed dispersers, and natural disturbance regimes.

Hofmeister series salts enhance purification of plasmid DNA by non-ionic detergents

PubMed Central

Lezin, George; Kuehn, Michael R.; Brunelli, Luca

2011-01-01

Ion-exchange chromatography is the standard technique used for plasmid DNA purification, an essential molecular biology procedure. Non-ionic detergents (NIDs) have been used for plasmid DNA purification, but it is unclear whether Hofmeister series salts (HSS) change the solubility and phase separation properties of specific NIDs, enhancing plasmid DNA purification. After scaling-up NID-mediated plasmid DNA isolation, we established that NIDs in HSS solutions minimize plasmid DNA contamination with protein. In addition, large-scale NID/HSS solutions eliminated LPS contamination of plasmid DNA more effectively than Qiagen ion-exchange columns. Large-scale NID isolation/NID purification generated increased yields of high quality DNA compared to alkali isolation/column purification. This work characterizes how HSS enhance NID-mediated plasmid DNA purification, and demonstrates that NID phase transition is not necessary for LPS removal from plasmid DNA. Specific NIDs such as IGEPAL CA-520 can be utilized for rapid, inexpensive and efficient laboratory-based large-scale plasmid DNA purification, outperforming Qiagen-based column procedures. PMID:21351074

Investigating the Potential of Deep Neural Networks for Large-Scale Classification of Very High Resolution Satellite Images

NASA Astrophysics Data System (ADS)

Postadjian, T.; Le Bris, A.; Sahbi, H.; Mallet, C.

2017-05-01

Semantic classification is a core remote sensing task as it provides the fundamental input for land-cover map generation. The very recent literature has shown the superior performance of deep convolutional neural networks (DCNN) for many classification tasks including the automatic analysis of Very High Spatial Resolution (VHR) geospatial images. Most of the recent initiatives have focused on very high discrimination capacity combined with accurate object boundary retrieval. Therefore, current architectures are perfectly tailored for urban areas over restricted areas but not designed for large-scale purposes. This paper presents an end-to-end automatic processing chain, based on DCNNs, that aims at performing large-scale classification of VHR satellite images (here SPOT 6/7). Since this work assesses, through various experiments, the potential of DCNNs for country-scale VHR land-cover map generation, a simple yet effective architecture is proposed, efficiently discriminating the main classes of interest (namely buildings, roads, water, crops, vegetated areas) by exploiting existing VHR land-cover maps for training.

Efficient production of human acidic fibroblast growth factor in pea (Pisum sativum L.) plants by agroinfection of germinated seeds

PubMed Central

2011-01-01

Background For efficient and large scale production of recombinant proteins in plants transient expression by agroinfection has a number of advantages over stable transformation. Simple manipulation, rapid analysis and high expression efficiency are possible. In pea, Pisum sativum, a Virus Induced Gene Silencing System using the pea early browning virus has been converted into an efficient agroinfection system by converting the two RNA genomes of the virus into binary expression vectors for Agrobacterium transformation. Results By vacuum infiltration (0.08 Mpa, 1 min) of germinating pea seeds with 2-3 cm roots with Agrobacteria carrying the binary vectors, expression of the gene for Green Fluorescent Protein as marker and the gene for the human acidic fibroblast growth factor (aFGF) was obtained in 80% of the infiltrated developing seedlings. Maximal production of the recombinant proteins was achieved 12-15 days after infiltration. Conclusions Compared to the leaf injection method vacuum infiltration of germinated seeds is highly efficient allowing large scale production of plants transiently expressing recombinant proteins. The production cycle of plants for harvesting the recombinant protein was shortened from 30 days for leaf injection to 15 days by applying vacuum infiltration. The synthesized aFGF was purified by heparin-affinity chromatography and its mitogenic activity on NIH 3T3 cells confirmed to be similar to a commercial product. PMID:21548923

An Improved Single-Step Cloning Strategy Simplifies the Agrobacterium tumefaciens-Mediated Transformation (ATMT)-Based Gene-Disruption Method for Verticillium dahliae.

PubMed

Wang, Sheng; Xing, Haiying; Hua, Chenlei; Guo, Hui-Shan; Zhang, Jie

2016-06-01

The soilborne fungal pathogen Verticillium dahliae infects a broad range of plant species to cause severe diseases. The availability of Verticillium genome sequences has provided opportunities for large-scale investigations of individual gene function in Verticillium strains using Agrobacterium tumefaciens-mediated transformation (ATMT)-based gene-disruption strategies. Traditional ATMT vectors require multiple cloning steps and elaborate characterization procedures to achieve successful gene replacement; thus, these vectors are not suitable for high-throughput ATMT-based gene deletion. Several advancements have been made that either involve simplification of the steps required for gene-deletion vector construction or increase the efficiency of the technique for rapid recombinant characterization. However, an ATMT binary vector that is both simple and efficient is still lacking. Here, we generated a USER-ATMT dual-selection (DS) binary vector, which combines both the advantages of the USER single-step cloning technique and the efficiency of the herpes simplex virus thymidine kinase negative-selection marker. Highly efficient deletion of three different genes in V. dahliae using the USER-ATMT-DS vector enabled verification that this newly-generated vector not only facilitates the cloning process but also simplifies the subsequent identification of fungal homologous recombinants. The results suggest that the USER-ATMT-DS vector is applicable for efficient gene deletion and suitable for large-scale gene deletion in V. dahliae.

Foster Wheeler's Solutions for Large Scale CFB Boiler Technology: Features and Operational Performance of Łagisza 460 MWe CFB Boiler

NASA Astrophysics Data System (ADS)

Hotta, Arto

During recent years, once-through supercritical (OTSC) CFB technology has been developed, enabling the CFB technology to proceed to medium-scale (500 MWe) utility projects such as Łagisza Power Plant in Poland owned by Poludniowy Koncern Energetyczny SA. (PKE), with net efficiency nearly 44%. Łagisza power plant is currently under commissioning and has reached full load operation in March 2009. The initial operation shows very good performance and confirms, that the CFB process has no problems with the scaling up to this size. Also the once-through steam cycle utilizing Siemens' vertical tube Benson technology has performed as predicted in the CFB process. Foster Wheeler has developed the CFB design further up to 800 MWe with net efficiency of ≥45%.

Study of Potential Cost Reductions Resulting from Super-Large-Scale Manufacturing of PV Modules: Final Subcontract Report, 7 August 2003--30 September 2004

DOE Office of Scientific and Technical Information (OSTI.GOV)

Keshner, M. S.; Arya, R.

2004-10-01

Hewlett Packard has created a design for a ''Solar City'' factory that will process 30 million sq. meters of glass panels per year and produce 2.1-3.6 GW of solar panels per year-100x the volume of a typical, thin-film, solar panel manufacturer in 2004. We have shown that with a reasonable selection of materials, and conservative assumptions, this ''Solar City'' can produce solar panels and hit the price target of $1.00 per peak watt (6.5x-8.5x lower than prices in 2004) as the total price for a complete and installed rooftop (or ground mounted) solar energy system. This breakthrough in the pricemore » of solar energy comes without the need for any significant new invention. It comes entirely from the manufacturing scale of a large plant and the cost savings inherent in operating at such a large manufacturing scale. We expect that further optimizations from these simple designs will lead to further improvements in cost. The manufacturing process and cost depend on the choice for the active layer that converts sunlight into electricity. The efficiency by which sunlight is converted into electricity can range from 7% to 15%. This parameter has a large effect on the overall price per watt. There are other impacts, as well, and we have attempted to capture them without creating undue distractions. Our primary purpose is to demonstrate the impact of large-scale manufacturing. This impact is largely independent of the choice of active layer. It is not our purpose to compare the pro's and con's for various types of active layers. Significant improvements in cost per watt can also come from scientific advances in active layers that lead to higher efficiency. But, again, our focus is on manufacturing gains and not on the potential advances in the basic technology.« less

Anderson acceleration of the Jacobi iterative method: An efficient alternative to Krylov methods for large, sparse linear systems

DOE PAGES

Pratapa, Phanisri P.; Suryanarayana, Phanish; Pask, John E.

2015-12-01

We employ Anderson extrapolation to accelerate the classical Jacobi iterative method for large, sparse linear systems. Specifically, we utilize extrapolation at periodic intervals within the Jacobi iteration to develop the Alternating Anderson–Jacobi (AAJ) method. We verify the accuracy and efficacy of AAJ in a range of test cases, including nonsymmetric systems of equations. We demonstrate that AAJ possesses a favorable scaling with system size that is accompanied by a small prefactor, even in the absence of a preconditioner. In particular, we show that AAJ is able to accelerate the classical Jacobi iteration by over four orders of magnitude, with speed-upsmore » that increase as the system gets larger. Moreover, we find that AAJ significantly outperforms the Generalized Minimal Residual (GMRES) method in the range of problems considered here, with the relative performance again improving with size of the system. As a result, the proposed method represents a simple yet efficient technique that is particularly attractive for large-scale parallel solutions of linear systems of equations.« less

Parallel group independent component analysis for massive fMRI data sets.

PubMed

Chen, Shaojie; Huang, Lei; Qiu, Huitong; Nebel, Mary Beth; Mostofsky, Stewart H; Pekar, James J; Lindquist, Martin A; Eloyan, Ani; Caffo, Brian S

2017-01-01

Independent component analysis (ICA) is widely used in the field of functional neuroimaging to decompose data into spatio-temporal patterns of co-activation. In particular, ICA has found wide usage in the analysis of resting state fMRI (rs-fMRI) data. Recently, a number of large-scale data sets have become publicly available that consist of rs-fMRI scans from thousands of subjects. As a result, efficient ICA algorithms that scale well to the increased number of subjects are required. To address this problem, we propose a two-stage likelihood-based algorithm for performing group ICA, which we denote Parallel Group Independent Component Analysis (PGICA). By utilizing the sequential nature of the algorithm and parallel computing techniques, we are able to efficiently analyze data sets from large numbers of subjects. We illustrate the efficacy of PGICA, which has been implemented in R and is freely available through the Comprehensive R Archive Network, through simulation studies and application to rs-fMRI data from two large multi-subject data sets, consisting of 301 and 779 subjects respectively.

Prospects, recent advancements and challenges of different wastewater streams for microalgal cultivation.

PubMed

Guldhe, Abhishek; Kumari, Sheena; Ramanna, Luveshan; Ramsundar, Prathana; Singh, Poonam; Rawat, Ismail; Bux, Faizal

2017-12-01

Microalgae are recognized as one of the most powerful biotechnology platforms for many value added products including biofuels, bioactive compounds, animal and aquaculture feed etc. However, large scale production of microalgal biomass poses challenges due to the requirements of large amounts of water and nutrients for cultivation. Using wastewater for microalgal cultivation has emerged as a potential cost effective strategy for large scale microalgal biomass production. This approach also offers an efficient means to remove nutrients and metals from wastewater making wastewater treatment sustainable and energy efficient. Therefore, much research has been conducted in the recent years on utilizing various wastewater streams for microalgae cultivation. This review identifies and discusses the opportunities and challenges of different wastewater streams for microalgal cultivation. Many alternative routes for microalgal cultivation have been proposed to tackle some of the challenges that occur during microalgal cultivation in wastewater such as nutrient deficiency, substrate inhibition, toxicity etc. Scope and challenges of microalgal biomass grown on wastewater for various applications are also discussed along with the biorefinery approach. Copyright © 2017 Elsevier Ltd. All rights reserved.

Anderson acceleration of the Jacobi iterative method: An efficient alternative to Krylov methods for large, sparse linear systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pratapa, Phanisri P.; Suryanarayana, Phanish; Pask, John E.

We employ Anderson extrapolation to accelerate the classical Jacobi iterative method for large, sparse linear systems. Specifically, we utilize extrapolation at periodic intervals within the Jacobi iteration to develop the Alternating Anderson–Jacobi (AAJ) method. We verify the accuracy and efficacy of AAJ in a range of test cases, including nonsymmetric systems of equations. We demonstrate that AAJ possesses a favorable scaling with system size that is accompanied by a small prefactor, even in the absence of a preconditioner. In particular, we show that AAJ is able to accelerate the classical Jacobi iteration by over four orders of magnitude, with speed-upsmore » that increase as the system gets larger. Moreover, we find that AAJ significantly outperforms the Generalized Minimal Residual (GMRES) method in the range of problems considered here, with the relative performance again improving with size of the system. As a result, the proposed method represents a simple yet efficient technique that is particularly attractive for large-scale parallel solutions of linear systems of equations.« less

Efficiency of parallel direct optimization

NASA Technical Reports Server (NTRS)

Janies, D. A.; Wheeler, W. C.

2001-01-01

Tremendous progress has been made at the level of sequential computation in phylogenetics. However, little attention has been paid to parallel computation. Parallel computing is particularly suited to phylogenetics because of the many ways large computational problems can be broken into parts that can be analyzed concurrently. In this paper, we investigate the scaling factors and efficiency of random addition and tree refinement strategies using the direct optimization software, POY, on a small (10 slave processors) and a large (256 slave processors) cluster of networked PCs running LINUX. These algorithms were tested on several data sets composed of DNA and morphology ranging from 40 to 500 taxa. Various algorithms in POY show fundamentally different properties within and between clusters. All algorithms are efficient on the small cluster for the 40-taxon data set. On the large cluster, multibuilding exhibits excellent parallel efficiency, whereas parallel building is inefficient. These results are independent of data set size. Branch swapping in parallel shows excellent speed-up for 16 slave processors on the large cluster. However, there is no appreciable speed-up for branch swapping with the further addition of slave processors (>16). This result is independent of data set size. Ratcheting in parallel is efficient with the addition of up to 32 processors in the large cluster. This result is independent of data set size. c2001 The Willi Hennig Society.

A user-friendly tool to transform large scale administrative data into wide table format using a MapReduce program with a Pig Latin based script.

PubMed

Horiguchi, Hiromasa; Yasunaga, Hideo; Hashimoto, Hideki; Ohe, Kazuhiko

2012-12-22

Secondary use of large scale administrative data is increasingly popular in health services and clinical research, where a user-friendly tool for data management is in great demand. MapReduce technology such as Hadoop is a promising tool for this purpose, though its use has been limited by the lack of user-friendly functions for transforming large scale data into wide table format, where each subject is represented by one row, for use in health services and clinical research. Since the original specification of Pig provides very few functions for column field management, we have developed a novel system called GroupFilterFormat to handle the definition of field and data content based on a Pig Latin script. We have also developed, as an open-source project, several user-defined functions to transform the table format using GroupFilterFormat and to deal with processing that considers date conditions. Having prepared dummy discharge summary data for 2.3 million inpatients and medical activity log data for 950 million events, we used the Elastic Compute Cloud environment provided by Amazon Inc. to execute processing speed and scaling benchmarks. In the speed benchmark test, the response time was significantly reduced and a linear relationship was observed between the quantity of data and processing time in both a small and a very large dataset. The scaling benchmark test showed clear scalability. In our system, doubling the number of nodes resulted in a 47% decrease in processing time. Our newly developed system is widely accessible as an open resource. This system is very simple and easy to use for researchers who are accustomed to using declarative command syntax for commercial statistical software and Structured Query Language. Although our system needs further sophistication to allow more flexibility in scripts and to improve efficiency in data processing, it shows promise in facilitating the application of MapReduce technology to efficient data processing with large scale administrative data in health services and clinical research.

Enterprise tools to promote interoperability: MonitoringResources.org supports design and documentation of large-scale, long-term monitoringprograms

NASA Astrophysics Data System (ADS)

Weltzin, J. F.; Scully, R. A.; Bayer, J.

2016-12-01

Individual natural resource monitoring programs have evolved in response to different organizational mandates, jurisdictional needs, issues and questions. We are establishing a collaborative forum for large-scale, long-term monitoring programs to identify opportunities where collaboration could yield efficiency in monitoring design, implementation, analyses, and data sharing. We anticipate these monitoring programs will have similar requirements - e.g. survey design, standardization of protocols and methods, information management and delivery - that could be met by enterprise tools to promote sustainability, efficiency and interoperability of information across geopolitical boundaries or organizational cultures. MonitoringResources.org, a project of the Pacific Northwest Aquatic Monitoring Partnership, provides an on-line suite of enterprise tools focused on aquatic systems in the Pacific Northwest Region of the United States. We will leverage on and expand this existing capacity to support continental-scale monitoring of both aquatic and terrestrial systems. The current stakeholder group is focused on programs led by bureaus with the Department of Interior, but the tools will be readily and freely available to a broad variety of other stakeholders. Here, we report the results of two initial stakeholder workshops focused on (1) establishing a collaborative forum of large scale monitoring programs, (2) identifying and prioritizing shared needs, (3) evaluating existing enterprise resources, (4) defining priorities for development of enhanced capacity for MonitoringResources.org, and (5) identifying a small number of pilot projects that can be used to define and test development requirements for specific monitoring programs.

Fire Whirls

NASA Astrophysics Data System (ADS)

Tohidi, Ali; Gollner, Michael J.; Xiao, Huahua

2018-01-01

Fire whirls present a powerful intensification of combustion, long studied in the fire research community because of the dangers they present during large urban and wildland fires. However, their destructive power has hidden many features of their formation, growth, and propagation. Therefore, most of what is known about fire whirls comes from scale modeling experiments in the laboratory. Both the methods of formation, which are dominated by wind and geometry, and the inner structure of the whirl, including velocity and temperature fields, have been studied at this scale. Quasi-steady fire whirls directly over a fuel source form the bulk of current experimental knowledge, although many other cases exist in nature. The structure of fire whirls has yet to be reliably measured at large scales; however, scaling laws have been relatively successful in modeling the conditions for formation from small to large scales. This review surveys the state of knowledge concerning the fluid dynamics of fire whirls, including the conditions for their formation, their structure, and the mechanisms that control their unique state. We highlight recent discoveries and survey potential avenues for future research, including using the properties of fire whirls for efficient remediation and energy generation.

SQDFT: Spectral Quadrature method for large-scale parallel O(N) Kohn-Sham calculations at high temperature

NASA Astrophysics Data System (ADS)

Suryanarayana, Phanish; Pratapa, Phanisri P.; Sharma, Abhiraj; Pask, John E.

2018-03-01

We present SQDFT: a large-scale parallel implementation of the Spectral Quadrature (SQ) method for O(N) Kohn-Sham Density Functional Theory (DFT) calculations at high temperature. Specifically, we develop an efficient and scalable finite-difference implementation of the infinite-cell Clenshaw-Curtis SQ approach, in which results for the infinite crystal are obtained by expressing quantities of interest as bilinear forms or sums of bilinear forms, that are then approximated by spatially localized Clenshaw-Curtis quadrature rules. We demonstrate the accuracy of SQDFT by showing systematic convergence of energies and atomic forces with respect to SQ parameters to reference diagonalization results, and convergence with discretization to established planewave results, for both metallic and insulating systems. We further demonstrate that SQDFT achieves excellent strong and weak parallel scaling on computer systems consisting of tens of thousands of processors, with near perfect O(N) scaling with system size and wall times as low as a few seconds per self-consistent field iteration. Finally, we verify the accuracy of SQDFT in large-scale quantum molecular dynamics simulations of aluminum at high temperature.

Suppressing turbulence of self-propelling rods by strongly coupled passive particles.

PubMed

Su, Yen-Shuo; Wang, Hao-Chen; I, Lin

2015-03-01

The strong turbulence suppression, mainly for large-scale modes, of two-dimensional self-propelling rods, by increasing the long-range coupling strength Γ of low-concentration passive particles, is numerically demonstrated. It is found that large-scale collective rod motion in forms of swirls or jets is mainly contributed from well-aligned dense patches, which can push small poorly aligned rod patches and uncoupled passive particles. The more efficient momentum transfer and dissipation through increasing passive particle coupling leads to the formation of a more ordered and slowed down network of passive particles, which competes with coherent dense active rod clusters. The frustration of active rod alignment ordering and coherent motion by the passive particle network, which interrupt the inverse cascading of forming large-scale swirls, is the key for suppressing collective rod motion with scales beyond the interpassive distance, even in the liquid phase of passive particles. The loosely packed active rods are weakly affected by increasing passive particle coupling due to the weak rod-particle interaction. They mainly contribute to the small-scale modes and high-speed motion.

Diazo compounds in continuous-flow technology.

PubMed

Müller, Simon T R; Wirth, Thomas

2015-01-01

Diazo compounds are very versatile reagents in organic chemistry and meet the challenge of selective assembly of structurally complex molecules. Their leaving group is dinitrogen; therefore, they are very clean and atom-efficient reagents. However, diazo compounds are potentially explosive and extremely difficult to handle on an industrial scale. In this review, it is discussed how continuous flow technology can help to make these powerful reagents accessible on large scale. Microstructured devices can improve heat transfer greatly and help with the handling of dangerous reagents safely. The in situ formation and subsequent consumption of diazo compounds are discussed along with advances in handling diazomethane and ethyl diazoacetate. The potential large-scale applications of a given methodology is emphasized. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Hi-Corrector: a fast, scalable and memory-efficient package for normalizing large-scale Hi-C data.

PubMed

Li, Wenyuan; Gong, Ke; Li, Qingjiao; Alber, Frank; Zhou, Xianghong Jasmine

2015-03-15

Genome-wide proximity ligation assays, e.g. Hi-C and its variant TCC, have recently become important tools to study spatial genome organization. Removing biases from chromatin contact matrices generated by such techniques is a critical preprocessing step of subsequent analyses. The continuing decline of sequencing costs has led to an ever-improving resolution of the Hi-C data, resulting in very large matrices of chromatin contacts. Such large-size matrices, however, pose a great challenge on the memory usage and speed of its normalization. Therefore, there is an urgent need for fast and memory-efficient methods for normalization of Hi-C data. We developed Hi-Corrector, an easy-to-use, open source implementation of the Hi-C data normalization algorithm. Its salient features are (i) scalability-the software is capable of normalizing Hi-C data of any size in reasonable times; (ii) memory efficiency-the sequential version can run on any single computer with very limited memory, no matter how little; (iii) fast speed-the parallel version can run very fast on multiple computing nodes with limited local memory. The sequential version is implemented in ANSI C and can be easily compiled on any system; the parallel version is implemented in ANSI C with the MPI library (a standardized and portable parallel environment designed for solving large-scale scientific problems). The package is freely available at http://zhoulab.usc.edu/Hi-Corrector/. © The Author 2014. Published by Oxford University Press.

Regional-scale calculation of the LS factor using parallel processing

NASA Astrophysics Data System (ADS)

Liu, Kai; Tang, Guoan; Jiang, Ling; Zhu, A.-Xing; Yang, Jianyi; Song, Xiaodong

2015-05-01

With the increase of data resolution and the increasing application of USLE over large areas, the existing serial implementation of algorithms for computing the LS factor is becoming a bottleneck. In this paper, a parallel processing model based on message passing interface (MPI) is presented for the calculation of the LS factor, so that massive datasets at a regional scale can be processed efficiently. The parallel model contains algorithms for calculating flow direction, flow accumulation, drainage network, slope, slope length and the LS factor. According to the existence of data dependence, the algorithms are divided into local algorithms and global algorithms. Parallel strategy are designed according to the algorithm characters including the decomposition method for maintaining the integrity of the results, optimized workflow for reducing the time taken for exporting the unnecessary intermediate data and a buffer-communication-computation strategy for improving the communication efficiency. Experiments on a multi-node system show that the proposed parallel model allows efficient calculation of the LS factor at a regional scale with a massive dataset.

Quantum Monte Carlo for large chemical systems: implementing efficient strategies for petascale platforms and beyond.

PubMed

Scemama, Anthony; Caffarel, Michel; Oseret, Emmanuel; Jalby, William

2013-04-30

Various strategies to implement efficiently quantum Monte Carlo (QMC) simulations for large chemical systems are presented. These include: (i) the introduction of an efficient algorithm to calculate the computationally expensive Slater matrices. This novel scheme is based on the use of the highly localized character of atomic Gaussian basis functions (not the molecular orbitals as usually done), (ii) the possibility of keeping the memory footprint minimal, (iii) the important enhancement of single-core performance when efficient optimization tools are used, and (iv) the definition of a universal, dynamic, fault-tolerant, and load-balanced framework adapted to all kinds of computational platforms (massively parallel machines, clusters, or distributed grids). These strategies have been implemented in the QMC=Chem code developed at Toulouse and illustrated with numerical applications on small peptides of increasing sizes (158, 434, 1056, and 1731 electrons). Using 10-80 k computing cores of the Curie machine (GENCI-TGCC-CEA, France), QMC=Chem has been shown to be capable of running at the petascale level, thus demonstrating that for this machine a large part of the peak performance can be achieved. Implementation of large-scale QMC simulations for future exascale platforms with a comparable level of efficiency is expected to be feasible. Copyright © 2013 Wiley Periodicals, Inc.

Large-scale linear rankSVM.

PubMed

Lee, Ching-Pei; Lin, Chih-Jen

2014-04-01

Linear rankSVM is one of the widely used methods for learning to rank. Although its performance may be inferior to nonlinear methods such as kernel rankSVM and gradient boosting decision trees, linear rankSVM is useful to quickly produce a baseline model. Furthermore, following its recent development for classification, linear rankSVM may give competitive performance for large and sparse data. A great deal of works have studied linear rankSVM. The focus is on the computational efficiency when the number of preference pairs is large. In this letter, we systematically study existing works, discuss their advantages and disadvantages, and propose an efficient algorithm. We discuss different implementation issues and extensions with detailed experiments. Finally, we develop a robust linear rankSVM tool for public use.

A comparative study of all-vanadium and iron-chromium redox flow batteries for large-scale energy storage

NASA Astrophysics Data System (ADS)

Zeng, Y. K.; Zhao, T. S.; An, L.; Zhou, X. L.; Wei, L.

2015-12-01

The promise of redox flow batteries (RFBs) utilizing soluble redox couples, such as all vanadium ions as well as iron and chromium ions, is becoming increasingly recognized for large-scale energy storage of renewables such as wind and solar, owing to their unique advantages including scalability, intrinsic safety, and long cycle life. An ongoing question associated with these two RFBs is determining whether the vanadium redox flow battery (VRFB) or iron-chromium redox flow battery (ICRFB) is more suitable and competitive for large-scale energy storage. To address this concern, a comparative study has been conducted for the two types of battery based on their charge-discharge performance, cycle performance, and capital cost. It is found that: i) the two batteries have similar energy efficiencies at high current densities; ii) the ICRFB exhibits a higher capacity decay rate than does the VRFB; and iii) the ICRFB is much less expensive in capital costs when operated at high power densities or at large capacities.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Manohar, AK; Yang, CG; Malkhandi, S

Iron-based alkaline rechargeable batteries have the potential of meeting the needs of large-scale electrical energy storage because of their low-cost, robustness and eco-friendliness. However, the widespread commercial deployment of iron-based batteries has been limited by the low charging efficiency and the poor discharge rate capability of the iron electrode. In this study, we have demonstrated iron electrodes containing bismuth oxide and iron sulfide with a charging efficiency of 92% and capable of being discharged at the 3C rate. Such a high value of charging efficiency combined with the ability to discharge at high rates is being reported for the firstmore » time. The bismuth oxide additive led to the in situ formation of elemental bismuth and a consequent increase in the overpotential for the hydrogen evolution reaction leading to an increase in the charging efficiency. We observed that the sulfide ions added to the electrolyte and iron sulfide added to the electrode mitigated-electrode passivation and allowed for continuous discharge at high rates. At the 3C discharge rate, a utilization of 0.2 Ah/g was achieved. The performance level of the rechargeable iron electrode demonstrated here is attractive for designing economically-viable large-scale energy storage systems based on alkaline nickel-iron and iron-air batteries. (C) 2013 The Electrochemical Society. All rights reserved.« less

High-Temperature-Short-Time Annealing Process for High-Performance Large-Area Perovskite Solar Cells.

PubMed

Kim, Minjin; Kim, Gi-Hwan; Oh, Kyoung Suk; Jo, Yimhyun; Yoon, Hyun; Kim, Ka-Hyun; Lee, Heon; Kim, Jin Young; Kim, Dong Suk

2017-06-27

Organic-inorganic hybrid metal halide perovskite solar cells (PSCs) are attracting tremendous research interest due to their high solar-to-electric power conversion efficiency with a high possibility of cost-effective fabrication and certified power conversion efficiency now exceeding 22%. Although many effective methods for their application have been developed over the past decade, their practical transition to large-size devices has been restricted by difficulties in achieving high performance. Here we report on the development of a simple and cost-effective production method with high-temperature and short-time annealing processing to obtain uniform, smooth, and large-size grain domains of perovskite films over large areas. With high-temperature short-time annealing at 400 °C for 4 s, the perovskite film with an average domain size of 1 μm was obtained, which resulted in fast solvent evaporation. Solar cells fabricated using this processing technique had a maximum power conversion efficiency exceeding 20% over a 0.1 cm 2 active area and 18% over a 1 cm 2 active area. We believe our approach will enable the realization of highly efficient large-area PCSs for practical development with a very simple and short-time procedure. This simple method should lead the field toward the fabrication of uniform large-scale perovskite films, which are necessary for the production of high-efficiency solar cells that may also be applicable to several other material systems for more widespread practical deployment.

Large-scale preparation of clove essential oil and eugenol-loaded liposomes using a membrane contactor and a pilot plant.

PubMed

Sebaaly, Carine; Greige-Gerges, Hélène; Agusti, Géraldine; Fessi, Hatem; Charcosset, Catherine

2016-01-01

Based on our previous study where optimal conditions were defined to encapsulate clove essential oil (CEO) into liposomes at laboratory scale, we scaled-up the preparation of CEO and eugenol (Eug)-loaded liposomes using a membrane contactor (600 mL) and a pilot plant (3 L) based on the principle of ethanol injection method, both equipped with a Shirasu Porous Glass membrane for injection of the organic phase into the aqueous phase. Homogenous, stable, nanometric-sized and multilamellar liposomes with high phospholipid, Eug loading rates and encapsulation efficiency of CEO components were obtained. Saturation of phospholipids and drug concentration in the organic phase may control the liposome stability. Liposomes loaded with other hydrophobic volatile compounds could be prepared at large scale using the ethanol injection method and a membrane for injection.

Simulation research on the process of large scale ship plane segmentation intelligent workshop

NASA Astrophysics Data System (ADS)

Xu, Peng; Liao, Liangchuang; Zhou, Chao; Xue, Rui; Fu, Wei

2017-04-01

Large scale ship plane segmentation intelligent workshop is a new thing, and there is no research work in related fields at home and abroad. The mode of production should be transformed by the existing industry 2.0 or part of industry 3.0, also transformed from "human brain analysis and judgment + machine manufacturing" to "machine analysis and judgment + machine manufacturing". In this transforming process, there are a great deal of tasks need to be determined on the aspects of management and technology, such as workshop structure evolution, development of intelligent equipment and changes in business model. Along with them is the reformation of the whole workshop. Process simulation in this project would verify general layout and process flow of large scale ship plane section intelligent workshop, also would analyze intelligent workshop working efficiency, which is significant to the next step of the transformation of plane segmentation intelligent workshop.

Fuel savings and emissions reductions from light duty fuel cell vehicles

NASA Astrophysics Data System (ADS)

Mark, J.; Ohi, J. M.; Hudson, D. V., Jr.

1994-04-01

Fuel cell vehicles (FCV's) operate efficiently, emit few pollutants, and run on nonpetroleum fuels. Because of these characteristics, the large-scale deployment of FCV's has the potential to lessen U.S. dependence on foreign oil and improve air quality. This study characterizes the benefits of large-scale FCV deployment in the light duty vehicle market. Specifically, the study assesses the potential fuel savings and emissions reductions resulting from large-scale use of these FCV's and identifies the key parameters that affect the scope of the benefits from FCV use. The analysis scenario assumes that FCV's will compete with gasoline-powered light trucks and cars in the new vehicle market for replacement of retired vehicles and will compete for growth in the total market. Analysts concluded that the potential benefits from FCV's, measured in terms of consumer outlays for motor fuel and the value of reduced air emissions, are substantial.

Solving large-scale fixed cost integer linear programming models for grid-based location problems with heuristic techniques

NASA Astrophysics Data System (ADS)

Noor-E-Alam, Md.; Doucette, John

2015-08-01

Grid-based location problems (GBLPs) can be used to solve location problems in business, engineering, resource exploitation, and even in the field of medical sciences. To solve these decision problems, an integer linear programming (ILP) model is designed and developed to provide the optimal solution for GBLPs considering fixed cost criteria. Preliminary results show that the ILP model is efficient in solving small to moderate-sized problems. However, this ILP model becomes intractable in solving large-scale instances. Therefore, a decomposition heuristic is proposed to solve these large-scale GBLPs, which demonstrates significant reduction of solution runtimes. To benchmark the proposed heuristic, results are compared with the exact solution via ILP. The experimental results show that the proposed method significantly outperforms the exact method in runtime with minimal (and in most cases, no) loss of optimality.

Sub-Selective Quantization for Learning Binary Codes in Large-Scale Image Search.

PubMed

Li, Yeqing; Liu, Wei; Huang, Junzhou

2018-06-01

Recently with the explosive growth of visual content on the Internet, large-scale image search has attracted intensive attention. It has been shown that mapping high-dimensional image descriptors to compact binary codes can lead to considerable efficiency gains in both storage and performing similarity computation of images. However, most existing methods still suffer from expensive training devoted to large-scale binary code learning. To address this issue, we propose a sub-selection based matrix manipulation algorithm, which can significantly reduce the computational cost of code learning. As case studies, we apply the sub-selection algorithm to several popular quantization techniques including cases using linear and nonlinear mappings. Crucially, we can justify the resulting sub-selective quantization by proving its theoretic properties. Extensive experiments are carried out on three image benchmarks with up to one million samples, corroborating the efficacy of the sub-selective quantization method in terms of image retrieval.

Parallel Simulation of Unsteady Turbulent Flames

NASA Technical Reports Server (NTRS)

Menon, Suresh

1996-01-01

Time-accurate simulation of turbulent flames in high Reynolds number flows is a challenging task since both fluid dynamics and combustion must be modeled accurately. To numerically simulate this phenomenon, very large computer resources (both time and memory) are required. Although current vector supercomputers are capable of providing adequate resources for simulations of this nature, the high cost and their limited availability, makes practical use of such machines less than satisfactory. At the same time, the explicit time integration algorithms used in unsteady flow simulations often possess a very high degree of parallelism, making them very amenable to efficient implementation on large-scale parallel computers. Under these circumstances, distributed memory parallel computers offer an excellent near-term solution for greatly increased computational speed and memory, at a cost that may render the unsteady simulations of the type discussed above more feasible and affordable.This paper discusses the study of unsteady turbulent flames using a simulation algorithm that is capable of retaining high parallel efficiency on distributed memory parallel architectures. Numerical studies are carried out using large-eddy simulation (LES). In LES, the scales larger than the grid are computed using a time- and space-accurate scheme, while the unresolved small scales are modeled using eddy viscosity based subgrid models. This is acceptable for the moment/energy closure since the small scales primarily provide a dissipative mechanism for the energy transferred from the large scales. However, for combustion to occur, the species must first undergo mixing at the small scales and then come into molecular contact. Therefore, global models cannot be used. Recently, a new model for turbulent combustion was developed, in which the combustion is modeled, within the subgrid (small-scales) using a methodology that simulates the mixing and the molecular transport and the chemical kinetics within each LES grid cell. Finite-rate kinetics can be included without any closure and this approach actually provides a means to predict the turbulent rates and the turbulent flame speed. The subgrid combustion model requires resolution of the local time scales associated with small-scale mixing, molecular diffusion and chemical kinetics and, therefore, within each grid cell, a significant amount of computations must be carried out before the large-scale (LES resolved) effects are incorporated. Therefore, this approach is uniquely suited for parallel processing and has been implemented on various systems such as: Intel Paragon, IBM SP-2, Cray T3D and SGI Power Challenge (PC) using the system independent Message Passing Interface (MPI) compiler. In this paper, timing data on these machines is reported along with some characteristic results.

Increased glycosylation efficiency of recombinant proteins in Escherichia coli by auto-induction.

PubMed

Ding, Ning; Yang, Chunguang; Sun, Shenxia; Han, Lichi; Ruan, Yao; Guo, Longhua; Hu, Xuejun; Zhang, Jianing

2017-03-25

Escherichia coli cells have been considered as promising hosts for producing N-glycosylated proteins since the successful production of N-glycosylated protein in E. coli with the pgl (N-linked protein glycosylation) locus from Campylobacter jejuni. However, one hurdle in producing N-glycosylated proteins in large scale using E. coli is inefficient glycan glycosylation. In this study, we developed a strategy for the production of N-glycosylated proteins with high efficiency via an optimized auto-induction method. The 10th human fibronectin type III domain (FN3) was engineered with native glycosylation sequon DFNRSK and optimized DQNAT sequon in C-terminus with flexible linker as acceptor protein models. The resulting glycosylation efficiencies were confirmed by Western blots with anti-FLAG M1 antibody. Increased efficiency of glycosylation was obtained by changing the conventional IPTG induction to auto-induction method, which increased the glycosylation efficiencies from 60% and 75% up to 90% and 100% respectively. Moreover, in the condition of inserting the glycosylation sequon in the loop of FN3 (the acceptor sequon with local structural conformation), the glycosylation efficiency was increased from 35% to 80% by our optimized auto-induction procedures. To justify the potential for general application of the optimized auto-induction method, the reconstituted lsg locus from Haemophilus influenzae and PglB from C. jejuni were utilized, and this led to 100% glycosylation efficiency. Our studies provided quantitative evidence that the optimized auto-induction method will facilitate the large-scale production of pure exogenous N-glycosylation proteins in E. coli cells. Copyright © 2017 Elsevier Inc. All rights reserved.

Robot vibration control using inertial damping forces

NASA Technical Reports Server (NTRS)

Lee, Soo Han; Book, Wayne J.

1991-01-01

This paper concerns the suppression of the vibration of a large flexible robot by inertial forces of a small robot which is located at the tip of the large robot. A controller for generating damping forces to a large robot is designed based on the two time scale model. The controller does not need to calculate the quasi-steady variables and is efficient in computation. Simulation results show the effectiveness of the inertial forces and the controller designed.

Robot vibration control using inertial damping forces

NASA Technical Reports Server (NTRS)

Lee, Soo Han; Book, Wayne J.

1989-01-01

The suppression is examined of the vibration of a large flexible robot by inertial forces of a small robot which is located at the tip of the large robot. A controller for generating damping forces to a large robot is designed based on the two time scale mode. The controller does not need to calculate the quasi-steady state variables and is efficient in computation. Simulation results show the effectiveness of the inertial forces and the controller designed.

Effect of the temperature and the CO2 concentration on the behaviour of the citric acid as a scale inhibitor of CaCO3

NASA Astrophysics Data System (ADS)

Blanco, K.; Aponte, H.; Vera, E.

2017-12-01

For all Industrial sector is important to extend the useful life of the materials that they use in their process, the scales of CaCO3 are common in situation where fluids are handled with high concentration of ions and besides this temperatures and CO2 concentration dissolved, that scale generates large annual losses because there is a reduction in the process efficiency or corrosion damage under deposit, among other. In order to find new alternatives to this problem, the citric acid was evaluated as scale of calcium carbonate inhibition in critical condition of temperature and concentration of CO2 dissolved. Once the results are obtained it was carried out the statistical evaluation in order to generate an equation that allow to see that behaviour, giving as result, a good efficiency of inhibition to the conditions evaluated the scales of products obtained were characterized through scanning electron microscopy.

75 FR 13765 - Submission for OMB Review; Use of Project Labor Agreements for Federal Construction Projects

Federal Register 2010, 2011, 2012, 2013, 2014

2010-03-23

... a project labor agreement (PLA), as they may decide appropriate, on large-scale construction... efficiency in Federal procurement. A PLA is a pre-hire collective bargaining agreement with one or more labor...

Multi-scale Material Appearance

NASA Astrophysics Data System (ADS)

Wu, Hongzhi

Modeling and rendering the appearance of materials is important for a diverse range of applications of computer graphics - from automobile design to movies and cultural heritage. The appearance of materials varies considerably at different scales, posing significant challenges due to the sheer complexity of the data, as well the need to maintain inter-scale consistency constraints. This thesis presents a series of studies around the modeling, rendering and editing of multi-scale material appearance. To efficiently render material appearance at multiple scales, we develop an object-space precomputed adaptive sampling method, which precomputes a hierarchy of view-independent points that preserve multi-level appearance. To support bi-scale material appearance design, we propose a novel reflectance filtering algorithm, which rapidly computes the large-scale appearance from small-scale details, by exploiting the low-rank structures of Bidirectional Visible Normal Distribution Functions and pre-rotated Bidirectional Reflectance Distribution Functions in the matrix formulation of the rendering algorithm. This approach can guide the physical realization of appearance, as well as the modeling of real-world materials using very sparse measurements. Finally, we present a bi-scale-inspired high-quality general representation for material appearance described by Bidirectional Texture Functions. Our representation is at once compact, easily editable, and amenable to efficient rendering.

Strategies for Energy Efficient Resource Management of Hybrid Programming Models

DOE Office of Scientific and Technical Information (OSTI.GOV)

Li, Dong; Supinski, Bronis de; Schulz, Martin

2013-01-01

Many scientific applications are programmed using hybrid programming models that use both message-passing and shared-memory, due to the increasing prevalence of large-scale systems with multicore, multisocket nodes. Previous work has shown that energy efficiency can be improved using software-controlled execution schemes that consider both the programming model and the power-aware execution capabilities of the system. However, such approaches have focused on identifying optimal resource utilization for one programming model, either shared-memory or message-passing, in isolation. The potential solution space, thus the challenge, increases substantially when optimizing hybrid models since the possible resource configurations increase exponentially. Nonetheless, with the accelerating adoptionmore » of hybrid programming models, we increasingly need improved energy efficiency in hybrid parallel applications on large-scale systems. In this work, we present new software-controlled execution schemes that consider the effects of dynamic concurrency throttling (DCT) and dynamic voltage and frequency scaling (DVFS) in the context of hybrid programming models. Specifically, we present predictive models and novel algorithms based on statistical analysis that anticipate application power and time requirements under different concurrency and frequency configurations. We apply our models and methods to the NPB MZ benchmarks and selected applications from the ASC Sequoia codes. Overall, we achieve substantial energy savings (8.74% on average and up to 13.8%) with some performance gain (up to 7.5%) or negligible performance loss.« less

The latest developments and outlook for hydrogen liquefaction technology

NASA Astrophysics Data System (ADS)

Ohlig, K.; Decker, L.

2014-01-01

Liquefied hydrogen is presently mainly used for space applications and the semiconductor industry. While clean energy applications, for e.g. the automotive sector, currently contribute to this demand with a small share only, their demand may see a significant boost in the next years with the need for large scale liquefaction plants exceeding the current plant sizes by far. Hydrogen liquefaction for small scale plants with a maximum capacity of 3 tons per day (tpd) is accomplished with a Brayton refrigeration cycle using helium as refrigerant. This technology is characterized by low investment costs but lower process efficiency and hence higher operating costs. For larger plants, a hydrogen Claude cycle is used, characterized by higher investment but lower operating costs. However, liquefaction plants meeting the potentially high demand in the clean energy sector will need further optimization with regard to energy efficiency and hence operating costs. The present paper gives an overview of the currently applied technologies, including their thermodynamic and technical background. Areas of improvement are identified to derive process concepts for future large scale hydrogen liquefaction plants meeting the needs of clean energy applications with optimized energy efficiency and hence minimized operating costs. Compared to studies in this field, this paper focuses on application of new technology and innovative concepts which are either readily available or will require short qualification procedures. They will hence allow implementation in plants in the close future.

DGDFT: A massively parallel method for large scale density functional theory calculations.

PubMed

Hu, Wei; Lin, Lin; Yang, Chao

2015-09-28

We describe a massively parallel implementation of the recently developed discontinuous Galerkin density functional theory (DGDFT) method, for efficient large-scale Kohn-Sham DFT based electronic structure calculations. The DGDFT method uses adaptive local basis (ALB) functions generated on-the-fly during the self-consistent field iteration to represent the solution to the Kohn-Sham equations. The use of the ALB set provides a systematic way to improve the accuracy of the approximation. By using the pole expansion and selected inversion technique to compute electron density, energy, and atomic forces, we can make the computational complexity of DGDFT scale at most quadratically with respect to the number of electrons for both insulating and metallic systems. We show that for the two-dimensional (2D) phosphorene systems studied here, using 37 basis functions per atom allows us to reach an accuracy level of 1.3 × 10(-4) Hartree/atom in terms of the error of energy and 6.2 × 10(-4) Hartree/bohr in terms of the error of atomic force, respectively. DGDFT can achieve 80% parallel efficiency on 128,000 high performance computing cores when it is used to study the electronic structure of 2D phosphorene systems with 3500-14 000 atoms. This high parallel efficiency results from a two-level parallelization scheme that we will describe in detail.

Large-Scale Simulations of Plastic Neural Networks on Neuromorphic Hardware

PubMed Central

Knight, James C.; Tully, Philip J.; Kaplan, Bernhard A.; Lansner, Anders; Furber, Steve B.

2016-01-01

SpiNNaker is a digital, neuromorphic architecture designed for simulating large-scale spiking neural networks at speeds close to biological real-time. Rather than using bespoke analog or digital hardware, the basic computational unit of a SpiNNaker system is a general-purpose ARM processor, allowing it to be programmed to simulate a wide variety of neuron and synapse models. This flexibility is particularly valuable in the study of biological plasticity phenomena. A recently proposed learning rule based on the Bayesian Confidence Propagation Neural Network (BCPNN) paradigm offers a generic framework for modeling the interaction of different plasticity mechanisms using spiking neurons. However, it can be computationally expensive to simulate large networks with BCPNN learning since it requires multiple state variables for each synapse, each of which needs to be updated every simulation time-step. We discuss the trade-offs in efficiency and accuracy involved in developing an event-based BCPNN implementation for SpiNNaker based on an analytical solution to the BCPNN equations, and detail the steps taken to fit this within the limited computational and memory resources of the SpiNNaker architecture. We demonstrate this learning rule by learning temporal sequences of neural activity within a recurrent attractor network which we simulate at scales of up to 2.0 × 104 neurons and 5.1 × 107 plastic synapses: the largest plastic neural network ever to be simulated on neuromorphic hardware. We also run a comparable simulation on a Cray XC-30 supercomputer system and find that, if it is to match the run-time of our SpiNNaker simulation, the super computer system uses approximately 45× more power. This suggests that cheaper, more power efficient neuromorphic systems are becoming useful discovery tools in the study of plasticity in large-scale brain models. PMID:27092061

Generating descriptive visual words and visual phrases for large-scale image applications.

PubMed

Zhang, Shiliang; Tian, Qi; Hua, Gang; Huang, Qingming; Gao, Wen

2011-09-01

Bag-of-visual Words (BoWs) representation has been applied for various problems in the fields of multimedia and computer vision. The basic idea is to represent images as visual documents composed of repeatable and distinctive visual elements, which are comparable to the text words. Notwithstanding its great success and wide adoption, visual vocabulary created from single-image local descriptors is often shown to be not as effective as desired. In this paper, descriptive visual words (DVWs) and descriptive visual phrases (DVPs) are proposed as the visual correspondences to text words and phrases, where visual phrases refer to the frequently co-occurring visual word pairs. Since images are the carriers of visual objects and scenes, a descriptive visual element set can be composed by the visual words and their combinations which are effective in representing certain visual objects or scenes. Based on this idea, a general framework is proposed for generating DVWs and DVPs for image applications. In a large-scale image database containing 1506 object and scene categories, the visual words and visual word pairs descriptive to certain objects or scenes are identified and collected as the DVWs and DVPs. Experiments show that the DVWs and DVPs are informative and descriptive and, thus, are more comparable with the text words than the classic visual words. We apply the identified DVWs and DVPs in several applications including large-scale near-duplicated image retrieval, image search re-ranking, and object recognition. The combination of DVW and DVP performs better than the state of the art in large-scale near-duplicated image retrieval in terms of accuracy, efficiency and memory consumption. The proposed image search re-ranking algorithm: DWPRank outperforms the state-of-the-art algorithm by 12.4% in mean average precision and about 11 times faster in efficiency.

SparseMaps—A systematic infrastructure for reduced-scaling electronic structure methods. III. Linear-scaling multireference domain-based pair natural orbital N-electron valence perturbation theory

DOE Office of Scientific and Technical Information (OSTI.GOV)

Guo, Yang; Sivalingam, Kantharuban; Neese, Frank, E-mail: Frank.Neese@cec.mpg.de

2016-03-07

Multi-reference (MR) electronic structure methods, such as MR configuration interaction or MR perturbation theory, can provide reliable energies and properties for many molecular phenomena like bond breaking, excited states, transition states or magnetic properties of transition metal complexes and clusters. However, owing to their inherent complexity, most MR methods are still too computationally expensive for large systems. Therefore the development of more computationally attractive MR approaches is necessary to enable routine application for large-scale chemical systems. Among the state-of-the-art MR methods, second-order N-electron valence state perturbation theory (NEVPT2) is an efficient, size-consistent, and intruder-state-free method. However, there are still twomore » important bottlenecks in practical applications of NEVPT2 to large systems: (a) the high computational cost of NEVPT2 for large molecules, even with moderate active spaces and (b) the prohibitive cost for treating large active spaces. In this work, we address problem (a) by developing a linear scaling “partially contracted” NEVPT2 method. This development uses the idea of domain-based local pair natural orbitals (DLPNOs) to form a highly efficient algorithm. As shown previously in the framework of single-reference methods, the DLPNO concept leads to an enormous reduction in computational effort while at the same time providing high accuracy (approaching 99.9% of the correlation energy), robustness, and black-box character. In the DLPNO approach, the virtual space is spanned by pair natural orbitals that are expanded in terms of projected atomic orbitals in large orbital domains, while the inactive space is spanned by localized orbitals. The active orbitals are left untouched. Our implementation features a highly efficient “electron pair prescreening” that skips the negligible inactive pairs. The surviving pairs are treated using the partially contracted NEVPT2 formalism. A detailed comparison between the partial and strong contraction schemes is made, with conclusions that discourage the strong contraction scheme as a basis for local correlation methods due to its non-invariance with respect to rotations in the inactive and external subspaces. A minimal set of conservatively chosen truncation thresholds controls the accuracy of the method. With the default thresholds, about 99.9% of the canonical partially contracted NEVPT2 correlation energy is recovered while the crossover of the computational cost with the already very efficient canonical method occurs reasonably early; in linear chain type compounds at a chain length of around 80 atoms. Calculations are reported for systems with more than 300 atoms and 5400 basis functions.« less

Scalable Parameter Estimation for Genome-Scale Biochemical Reaction Networks

PubMed Central

Kaltenbacher, Barbara; Hasenauer, Jan

2017-01-01

Mechanistic mathematical modeling of biochemical reaction networks using ordinary differential equation (ODE) models has improved our understanding of small- and medium-scale biological processes. While the same should in principle hold for large- and genome-scale processes, the computational methods for the analysis of ODE models which describe hundreds or thousands of biochemical species and reactions are missing so far. While individual simulations are feasible, the inference of the model parameters from experimental data is computationally too intensive. In this manuscript, we evaluate adjoint sensitivity analysis for parameter estimation in large scale biochemical reaction networks. We present the approach for time-discrete measurement and compare it to state-of-the-art methods used in systems and computational biology. Our comparison reveals a significantly improved computational efficiency and a superior scalability of adjoint sensitivity analysis. The computational complexity is effectively independent of the number of parameters, enabling the analysis of large- and genome-scale models. Our study of a comprehensive kinetic model of ErbB signaling shows that parameter estimation using adjoint sensitivity analysis requires a fraction of the computation time of established methods. The proposed method will facilitate mechanistic modeling of genome-scale cellular processes, as required in the age of omics. PMID:28114351

Pollutant Transport and Fate: Relations Between Flow-paths and Downstream Impacts of Human Activities

NASA Astrophysics Data System (ADS)

Thorslund, J.; Jarsjo, J.; Destouni, G.

2017-12-01

The quality of freshwater resources is increasingly impacted by human activities. Humans also extensively change the structure of landscapes, which may alter natural hydrological processes. To manage and maintain freshwater of good water quality, it is critical to understand how pollutants are released into, transported and transformed within the hydrological system. Some key scientific questions include: What are net downstream impacts of pollutants across different hydroclimatic and human disturbance conditions, and on different scales? What are the functions within and between components of the landscape, such as wetlands, on mitigating pollutant load delivery to downstream recipients? We explore these questions by synthesizing results from several relevant case study examples of intensely human-impacted hydrological systems. These case study sites have been specifically evaluated in terms of net impact of human activities on pollutant input to the aquatic system, as well as flow-path distributions trough wetlands as a potential ecosystem service of pollutant mitigation. Results shows that although individual wetlands have high retention capacity, efficient net retention effects were not always achieved at a larger landscape scale. Evidence suggests that the function of wetlands as mitigation solutions to pollutant loads is largely controlled by large-scale parallel and circular flow-paths, through which multiple wetlands are interconnected in the landscape. To achieve net mitigation effects at large scale, a large fraction of the polluted large-scale flows must be transported through multiple connected wetlands. Although such large-scale flow interactions are critical for assessing water pollution spreading and fate through the landscape, our synthesis shows a frequent lack of knowledge at such scales. We suggest ways forward for addressing the mismatch between the large scales at which key pollutant pressures and water quality changes take place and the relatively scale at which most studies and implementations are currently made. These suggestions can help bridge critical knowledge gaps, as needed for improving water quality predictions and mitigation solutions under human and environmental changes.

Small-scale dynamo at low magnetic Prandtl numbers

NASA Astrophysics Data System (ADS)

Schober, Jennifer; Schleicher, Dominik; Bovino, Stefano; Klessen, Ralf S.

2012-12-01

The present-day Universe is highly magnetized, even though the first magnetic seed fields were most probably extremely weak. To explain the growth of the magnetic field strength over many orders of magnitude, fast amplification processes need to operate. The most efficient mechanism known today is the small-scale dynamo, which converts turbulent kinetic energy into magnetic energy leading to an exponential growth of the magnetic field. The efficiency of the dynamo depends on the type of turbulence indicated by the slope of the turbulence spectrum v(ℓ)∝ℓϑ, where v(ℓ) is the eddy velocity at a scale ℓ. We explore turbulent spectra ranging from incompressible Kolmogorov turbulence with ϑ=1/3 to highly compressible Burgers turbulence with ϑ=1/2. In this work, we analyze the properties of the small-scale dynamo for low magnetic Prandtl numbers Pm, which denotes the ratio of the magnetic Reynolds number, Rm, to the hydrodynamical one, Re. We solve the Kazantsev equation, which describes the evolution of the small-scale magnetic field, using the WKB approximation. In the limit of low magnetic Prandtl numbers, the growth rate is proportional to Rm(1-ϑ)/(1+ϑ). We furthermore discuss the critical magnetic Reynolds number Rmcrit, which is required for small-scale dynamo action. The value of Rmcrit is roughly 100 for Kolmogorov turbulence and 2700 for Burgers. Furthermore, we discuss that Rmcrit provides a stronger constraint in the limit of low Pm than it does for large Pm. We conclude that the small-scale dynamo can operate in the regime of low magnetic Prandtl numbers if the magnetic Reynolds number is large enough. Thus, the magnetic field amplification on small scales can take place in a broad range of physical environments and amplify week magnetic seed fields on short time scales.

Small-scale dynamo at low magnetic Prandtl numbers.

PubMed

Schober, Jennifer; Schleicher, Dominik; Bovino, Stefano; Klessen, Ralf S

2012-12-01

The present-day Universe is highly magnetized, even though the first magnetic seed fields were most probably extremely weak. To explain the growth of the magnetic field strength over many orders of magnitude, fast amplification processes need to operate. The most efficient mechanism known today is the small-scale dynamo, which converts turbulent kinetic energy into magnetic energy leading to an exponential growth of the magnetic field. The efficiency of the dynamo depends on the type of turbulence indicated by the slope of the turbulence spectrum v(ℓ)∝ℓ^{ϑ}, where v(ℓ) is the eddy velocity at a scale ℓ. We explore turbulent spectra ranging from incompressible Kolmogorov turbulence with ϑ=1/3 to highly compressible Burgers turbulence with ϑ=1/2. In this work, we analyze the properties of the small-scale dynamo for low magnetic Prandtl numbers Pm, which denotes the ratio of the magnetic Reynolds number, Rm, to the hydrodynamical one, Re. We solve the Kazantsev equation, which describes the evolution of the small-scale magnetic field, using the WKB approximation. In the limit of low magnetic Prandtl numbers, the growth rate is proportional to Rm^{(1-ϑ)/(1+ϑ)}. We furthermore discuss the critical magnetic Reynolds number Rm_{crit}, which is required for small-scale dynamo action. The value of Rm_{crit} is roughly 100 for Kolmogorov turbulence and 2700 for Burgers. Furthermore, we discuss that Rm_{crit} provides a stronger constraint in the limit of low Pm than it does for large Pm. We conclude that the small-scale dynamo can operate in the regime of low magnetic Prandtl numbers if the magnetic Reynolds number is large enough. Thus, the magnetic field amplification on small scales can take place in a broad range of physical environments and amplify week magnetic seed fields on short time scales.

Efficient Load Balancing and Data Remapping for Adaptive Grid Calculations

NASA Technical Reports Server (NTRS)

Oliker, Leonid; Biswas, Rupak

1997-01-01

Mesh adaption is a powerful tool for efficient unstructured- grid computations but causes load imbalance among processors on a parallel machine. We present a novel method to dynamically balance the processor workloads with a global view. This paper presents, for the first time, the implementation and integration of all major components within our dynamic load balancing strategy for adaptive grid calculations. Mesh adaption, repartitioning, processor assignment, and remapping are critical components of the framework that must be accomplished rapidly and efficiently so as not to cause a significant overhead to the numerical simulation. Previous results indicated that mesh repartitioning and data remapping are potential bottlenecks for performing large-scale scientific calculations. We resolve these issues and demonstrate that our framework remains viable on a large number of processors.

Improved actions and asymptotic scaling in lattice Yang-Mills theory

DOE Office of Scientific and Technical Information (OSTI.GOV)

Langfeld, Kurt

2007-11-01

Improved actions in SU(2) and SU(3) lattice gauge theories are investigated with an emphasis on asymptotic scaling. A new scheme for tadpole improvement is proposed. The standard but heuristic tadpole improvement emerges from a mean field approximation from the new approach. Scaling is investigated by means of the large distance static quark potential. Both the generic and the new tadpole scheme yield significant improvements on asymptotic scaling when compared with loop improved actions. A study of the rotational symmetry breaking terms, however, reveals that only the new improvement scheme efficiently eliminates the leading irrelevant term from the action.

Micron-scale lens array having diffracting structures

DOEpatents

Goldberg, Kenneth A

2013-10-29

A novel micron-scale lens, a microlens, is engineered to concentrate light efficiently onto an area of interest, such as a small, light-sensitive detector element in an integrated electronic device. Existing microlens designs imitate the form of large-scale lenses and are less effective at small sizes. The microlenses described herein have been designed to accommodate diffraction effects, which dominate the behavior of light at small length scales. Thus a new class of light-concentrating optical elements with much higher relative performance has been created. Furthermore, the new designs are much easier to fabricate than previous designs.

Humidity Distributions in Multilayered Walls of High-rise Buildings

NASA Astrophysics Data System (ADS)

Gamayunova, Olga; Musorina, Tatiana; Ishkov, Alexander

2018-03-01

The limitation of free territories in large cities is the main reason for the active development of high-rise construction. Given the large-scale projects of high-rise buildings in recent years in Russia and abroad and their huge energy consumption, one of the fundamental principles in the design and reconstruction is the use of energy-efficient technologies. The main heat loss in buildings occurs through enclosing structures. However, not always the heat-resistant wall will be energy-efficient and dry at the same time (perhaps waterlogging). Temperature and humidity distributions in multilayer walls were studied in the paper, and the interrelation of other thermophysical characteristics was analyzed.

Highly efficient mesophyll protoplast isolation and PEG-mediated transient gene expression for rapid and large-scale gene characterization in cassava (Manihot esculenta Crantz).

PubMed

Wu, Jun-Zheng; Liu, Qin; Geng, Xiao-Shan; Li, Kai-Mian; Luo, Li-Juan; Liu, Jin-Ping

2017-03-14

Cassava (Manihot esculenta Crantz) is a major crop extensively cultivated in the tropics as both an important source of calories and a promising source for biofuel production. Although stable gene expression have been used for transgenic breeding and gene function study, a quick, easy and large-scale transformation platform has been in urgent need for gene functional characterization, especially after the cassava full genome was sequenced. Fully expanded leaves from in vitro plantlets of Manihot esculenta were used to optimize the concentrations of cellulase R-10 and macerozyme R-10 for obtaining protoplasts with the highest yield and viability. Then, the optimum conditions (PEG4000 concentration and transfection time) were determined for cassava protoplast transient gene expression. In addition, the reliability of the established protocol was confirmed for subcellular protein localization. In this work we optimized the main influencing factors and developed an efficient mesophyll protoplast isolation and PEG-mediated transient gene expression in cassava. The suitable enzyme digestion system was established with the combination of 1.6% cellulase R-10 and 0.8% macerozyme R-10 for 16 h of digestion in the dark at 25 °C, resulting in the high yield (4.4 × 10 7 protoplasts/g FW) and vitality (92.6%) of mesophyll protoplasts. The maximum transfection efficiency (70.8%) was obtained with the incubation of the protoplasts/vector DNA mixture with 25% PEG4000 for 10 min. We validated the applicability of the system for studying the subcellular localization of MeSTP7 (an H + /monosaccharide cotransporter) with our transient expression protocol and a heterologous Arabidopsis transient gene expression system. We optimized the main influencing factors and developed an efficient mesophyll protoplast isolation and transient gene expression in cassava, which will facilitate large-scale characterization of genes and pathways in cassava.

Developing a scalable inert gas ion thruster

NASA Technical Reports Server (NTRS)

James, E.; Ramsey, W.; Steiner, G.

1982-01-01

Analytical studies to identify and then design a high performance scalable ion thruster operating with either argon or xenon for use in large space systems are presented. The magnetoelectrostatic containment concept is selected for its efficient ion generation capabilities. The iterative nature of the bounding magnetic fields allows the designer to scale both the diameter and length, so that the thruster can be adapted to spacecraft growth over time. Three different thruster assemblies (conical, hexagonal and hemispherical) are evaluated for a 12 cm diameter thruster and performance mapping of the various thruster configurations shows that conical discharge chambers produce the most efficient discharge operation, achieving argon efficiencies of 50-80% mass utilization at 240-310 eV/ion and xenon efficiencies of 60-97% at 240-280 eV/ion. Preliminary testing of the large 30 cm thruster, using argon propellant, indicates a 35% improvement over the 12 cm thruster in mass utilization efficiency. Since initial performance is found to be better than projected, a larger 50 cm thruster is already in the development stage.

Portable parallel stochastic optimization for the design of aeropropulsion components

NASA Technical Reports Server (NTRS)

Sues, Robert H.; Rhodes, G. S.

1994-01-01

This report presents the results of Phase 1 research to develop a methodology for performing large-scale Multi-disciplinary Stochastic Optimization (MSO) for the design of aerospace systems ranging from aeropropulsion components to complete aircraft configurations. The current research recognizes that such design optimization problems are computationally expensive, and require the use of either massively parallel or multiple-processor computers. The methodology also recognizes that many operational and performance parameters are uncertain, and that uncertainty must be considered explicitly to achieve optimum performance and cost. The objective of this Phase 1 research was to initialize the development of an MSO methodology that is portable to a wide variety of hardware platforms, while achieving efficient, large-scale parallelism when multiple processors are available. The first effort in the project was a literature review of available computer hardware, as well as review of portable, parallel programming environments. The first effort was to implement the MSO methodology for a problem using the portable parallel programming language, Parallel Virtual Machine (PVM). The third and final effort was to demonstrate the example on a variety of computers, including a distributed-memory multiprocessor, a distributed-memory network of workstations, and a single-processor workstation. Results indicate the MSO methodology can be well-applied towards large-scale aerospace design problems. Nearly perfect linear speedup was demonstrated for computation of optimization sensitivity coefficients on both a 128-node distributed-memory multiprocessor (the Intel iPSC/860) and a network of workstations (speedups of almost 19 times achieved for 20 workstations). Very high parallel efficiencies (75 percent for 31 processors and 60 percent for 50 processors) were also achieved for computation of aerodynamic influence coefficients on the Intel. Finally, the multi-level parallelization strategy that will be needed for large-scale MSO problems was demonstrated to be highly efficient. The same parallel code instructions were used on both platforms, demonstrating portability. There are many applications for which MSO can be applied, including NASA's High-Speed-Civil Transport, and advanced propulsion systems. The use of MSO will reduce design and development time and testing costs dramatically.

Sunlight-thin nanophotonic monocrystalline silicon solar cells

NASA Astrophysics Data System (ADS)

Depauw, Valérie; Trompoukis, Christos; Massiot, Inès; Chen, Wanghua; Dmitriev, Alexandre; Cabarrocas, Pere Roca i.; Gordon, Ivan; Poortmans, Jef

2017-09-01

Introducing nanophotonics into photovoltaics sets the path for scaling down the surface texture of crystalline-silicon solar cells from the micro- to the nanoscale, allowing to further boost the photon absorption while reducing silicon material loss. However, keeping excellent electrical performance has proven to be very challenging, as the absorber is damaged by the nanotexturing and the sensitivity to the surface recombination is dramatically increased. Here we realize a light-wavelength-scale nanotextured monocrystalline silicon cell with the confirmed efficiency of 8.6% and an effective thickness of only 830 nm. For this we adopt a self-assembled large-area and industry-compatible amorphous ordered nanopatterning, combined with an advanced surface passivation, earning strongly enhanced solar light absorption while retaining efficient electron collection. This prompts the development of highly efficient flexible and semitransparent photovoltaics, based on the industrially mature monocrystalline silicon technology.

Self-consistent implementation of meta-GGA functionals for the ONETEP linear-scaling electronic structure package.

PubMed

Womack, James C; Mardirossian, Narbe; Head-Gordon, Martin; Skylaris, Chris-Kriton

2016-11-28

Accurate and computationally efficient exchange-correlation functionals are critical to the successful application of linear-scaling density functional theory (DFT). Local and semi-local functionals of the density are naturally compatible with linear-scaling approaches, having a general form which assumes the locality of electronic interactions and which can be efficiently evaluated by numerical quadrature. Presently, the most sophisticated and flexible semi-local functionals are members of the meta-generalized-gradient approximation (meta-GGA) family, and depend upon the kinetic energy density, τ, in addition to the charge density and its gradient. In order to extend the theoretical and computational advantages of τ-dependent meta-GGA functionals to large-scale DFT calculations on thousands of atoms, we have implemented support for τ-dependent meta-GGA functionals in the ONETEP program. In this paper we lay out the theoretical innovations necessary to implement τ-dependent meta-GGA functionals within ONETEP's linear-scaling formalism. We present expressions for the gradient of the τ-dependent exchange-correlation energy, necessary for direct energy minimization. We also derive the forms of the τ-dependent exchange-correlation potential and kinetic energy density in terms of the strictly localized, self-consistently optimized orbitals used by ONETEP. To validate the numerical accuracy of our self-consistent meta-GGA implementation, we performed calculations using the B97M-V and PKZB meta-GGAs on a variety of small molecules. Using only a minimal basis set of self-consistently optimized local orbitals, we obtain energies in excellent agreement with large basis set calculations performed using other codes. Finally, to establish the linear-scaling computational cost and applicability of our approach to large-scale calculations, we present the outcome of self-consistent meta-GGA calculations on amyloid fibrils of increasing size, up to tens of thousands of atoms.

Sparse maps—A systematic infrastructure for reduced-scaling electronic structure methods. II. Linear scaling domain based pair natural orbital coupled cluster theory

NASA Astrophysics Data System (ADS)

Riplinger, Christoph; Pinski, Peter; Becker, Ute; Valeev, Edward F.; Neese, Frank

2016-01-01

Domain based local pair natural orbital coupled cluster theory with single-, double-, and perturbative triple excitations (DLPNO-CCSD(T)) is a highly efficient local correlation method. It is known to be accurate and robust and can be used in a black box fashion in order to obtain coupled cluster quality total energies for large molecules with several hundred atoms. While previous implementations showed near linear scaling up to a few hundred atoms, several nonlinear scaling steps limited the applicability of the method for very large systems. In this work, these limitations are overcome and a linear scaling DLPNO-CCSD(T) method for closed shell systems is reported. The new implementation is based on the concept of sparse maps that was introduced in Part I of this series [P. Pinski, C. Riplinger, E. F. Valeev, and F. Neese, J. Chem. Phys. 143, 034108 (2015)]. Using the sparse map infrastructure, all essential computational steps (integral transformation and storage, initial guess, pair natural orbital construction, amplitude iterations, triples correction) are achieved in a linear scaling fashion. In addition, a number of additional algorithmic improvements are reported that lead to significant speedups of the method. The new, linear-scaling DLPNO-CCSD(T) implementation typically is 7 times faster than the previous implementation and consumes 4 times less disk space for large three-dimensional systems. For linear systems, the performance gains and memory savings are substantially larger. Calculations with more than 20 000 basis functions and 1000 atoms are reported in this work. In all cases, the time required for the coupled cluster step is comparable to or lower than for the preceding Hartree-Fock calculation, even if this is carried out with the efficient resolution-of-the-identity and chain-of-spheres approximations. The new implementation even reduces the error in absolute correlation energies by about a factor of two, compared to the already accurate previous implementation.

Self-consistent implementation of meta-GGA functionals for the ONETEP linear-scaling electronic structure package

NASA Astrophysics Data System (ADS)

Womack, James C.; Mardirossian, Narbe; Head-Gordon, Martin; Skylaris, Chris-Kriton

2016-11-01

Accurate and computationally efficient exchange-correlation functionals are critical to the successful application of linear-scaling density functional theory (DFT). Local and semi-local functionals of the density are naturally compatible with linear-scaling approaches, having a general form which assumes the locality of electronic interactions and which can be efficiently evaluated by numerical quadrature. Presently, the most sophisticated and flexible semi-local functionals are members of the meta-generalized-gradient approximation (meta-GGA) family, and depend upon the kinetic energy density, τ, in addition to the charge density and its gradient. In order to extend the theoretical and computational advantages of τ-dependent meta-GGA functionals to large-scale DFT calculations on thousands of atoms, we have implemented support for τ-dependent meta-GGA functionals in the ONETEP program. In this paper we lay out the theoretical innovations necessary to implement τ-dependent meta-GGA functionals within ONETEP's linear-scaling formalism. We present expressions for the gradient of the τ-dependent exchange-correlation energy, necessary for direct energy minimization. We also derive the forms of the τ-dependent exchange-correlation potential and kinetic energy density in terms of the strictly localized, self-consistently optimized orbitals used by ONETEP. To validate the numerical accuracy of our self-consistent meta-GGA implementation, we performed calculations using the B97M-V and PKZB meta-GGAs on a variety of small molecules. Using only a minimal basis set of self-consistently optimized local orbitals, we obtain energies in excellent agreement with large basis set calculations performed using other codes. Finally, to establish the linear-scaling computational cost and applicability of our approach to large-scale calculations, we present the outcome of self-consistent meta-GGA calculations on amyloid fibrils of increasing size, up to tens of thousands of atoms.

Computer-aided design of large-scale integrated circuits - A concept

NASA Technical Reports Server (NTRS)

Schansman, T. T.

1971-01-01

Circuit design and mask development sequence are improved by using general purpose computer with interactive graphics capability establishing efficient two way communications link between design engineer and system. Interactive graphics capability places design engineer in direct control of circuit development.

Intelligent switching between different noise propagation algorithms: analysis and sensitivity

DOT National Transportation Integrated Search

2012-08-10

When modeling aircraft noise on a large scale (such as an analysis of annual aircraft : operations at an airport), it is important that the noise propagation model used for the : analysis be both efficient and accurate. In this analysis, three differ...

Toward a more efficient and scalable checkpoint/restart mechanism in the Community Atmosphere Model

NASA Astrophysics Data System (ADS)

Anantharaj, Valentine

2015-04-01

The number of cores (both CPU as well as accelerator) in large-scale systems has been increasing rapidly over the past several years. In 2008, there were only 5 systems in the Top500 list that had over 100,000 total cores (including accelerator cores) whereas the number of system with such capability has jumped to 31 in Nov 2014. This growth however has also increased the risk of hardware failure rates, necessitating the implementation of fault tolerance mechanism in applications. The checkpoint and restart (C/R) approach is commonly used to save the state of the application and restart at a later time either after failure or to continue execution of experiments. The implementation of an efficient C/R mechanism will make it more affordable to output the necessary C/R files more frequently. The availability of larger systems (more nodes, memory and cores) has also facilitated the scaling of applications. Nowadays, it is more common to conduct coupled global climate simulation experiments at 1 deg horizontal resolution (atmosphere), often requiring about 103 cores. At the same time, a few climate modeling teams that have access to a dedicated cluster and/or large scale systems are involved in modeling experiments at 0.25 deg horizontal resolution (atmosphere) and 0.1 deg resolution for the ocean. These ultrascale configurations require the order of 104 to 105 cores. It is not only necessary for the numerical algorithms to scale efficiently but the input/output (IO) mechanism must also scale accordingly. An ongoing series of ultrascale climate simulations, using the Titan supercomputer at the Oak Ridge Leadership Computing Facility (ORNL), is based on the spectral element dynamical core of the Community Atmosphere Model (CAM-SE), which is a component of the Community Earth System Model and the DOE Accelerated Climate Model for Energy (ACME). The CAM-SE dynamical core for a 0.25 deg configuration has been shown to scale efficiently across 100,000 cpu cores. At this scale, there is an increased risk that the simulation could be terminated due to hardware failures, resulting in a loss that could be as high as 105 - 106 titan core hours. Increasing the frequency of the output of C/R files could mitigate this loss but at the cost of additional C/R overhead. We are testing a more efficient C/R mechanism in CAM-SE. Our early implementation has demonstrated a nearly 3X performance improvement for a 1 deg CAM-SE (with CAM5 physics and MOZART chemistry) configuration using nearly 103 cores. We are in the process of scaling our implementation to 105 cores. This would allow us to run ultra scale simulations with more sophisticated physics and chemistry options while making better utilization of resources.

Streaming fragment assignment for real-time analysis of sequencing experiments

PubMed Central

Roberts, Adam; Pachter, Lior

2013-01-01

We present eXpress, a software package for highly efficient probabilistic assignment of ambiguously mapping sequenced fragments. eXpress uses a streaming algorithm with linear run time and constant memory use. It can determine abundances of sequenced molecules in real time, and can be applied to ChIP-seq, metagenomics and other large-scale sequencing data. We demonstrate its use on RNA-seq data, showing greater efficiency than other quantification methods. PMID:23160280

High Efficiency Thermoelectric Materials and Devices

NASA Technical Reports Server (NTRS)

Kochergin, Vladimir (Inventor)

2013-01-01

Growth of thermoelectric materials in the form of quantum well super-lattices on three-dimensionally structured substrates provide the means to achieve high conversion efficiency of the thermoelectric module combined with inexpensiveness of fabrication and compatibility with large scale production. Thermoelectric devices utilizing thermoelectric materials in the form of quantum well semiconductor super-lattices grown on three-dimensionally structured substrates provide improved thermoelectric characteristics that can be used for power generation, cooling and other applications..

Integration and Improvement of Geophysical Root Biomass Measurements for Determining Carbon Credits

NASA Astrophysics Data System (ADS)

Boitet, J. I.

2013-12-01

Carbon trading schemes fundamentally rely on accurate subsurface carbon quantification in order for governing bodies to grant carbon credits inclusive of root biomass (What is Carbon Credit. 2013). Root biomass makes up a large chunk of the subsurface carbon and is difficult, labor intensive, and costly to measure. This paper stitches together the latest geophysical root measurement techniques into site-dependent recommendations for technique combinations and modifications that maximize large-scale root biomass measurement accuracy and efficiency. "Accuracy" is maximized when actual root biomass is closest to measured root biomass. "Efficiency" is maximized when time, labor, and cost of measurement is minimized. Several combinations have emerged which satisfy both criteria under different site conditions. Use of ground penetrating radar (GPR) and/or electrical resistivity tomography (ERT) allow for large tracts of land to be surveyed under appropriate conditions. Among other characteristics, GPR does best with detecting coarse roots in dry soil. ERT does best in detecting roots in moist soils, but is especially limited by electrode configuration (Mancuso, S. 2012). Integration of these two technologies into a baseline protocol based on site-specific characteristics, especially soil moisture and plants species heterogeneity, will drastically theoretically increase efficiency and accuracy of root biomass measurements. Modifications of current measurement protocols using these existing techniques will also theoretically lead to drastic improvements in both accuracy and efficiency. These modifications, such as efficient 3D imaging by adding an identical electrode array perpendicular to the first array used in the Pulled Array Continuous Electrical Profiling (PACEP) technique for ERT, should allow for more widespread application of these techniques for understanding root biomass. Where whole-site measurement is not feasible either due to financial, equipment, or physical limitations, measurements from randomly selected plots must be assumed representative of the entire system and scaled up. This scaling introduces error roughly inversely proportional to the number and size of plots measured. References Mancuso, S. (2012). Measuring roots: An updated approach Springer. What is carbon credit. (2013). Retrieved 7/20, 2013, from http://carbontradexchange.com/knowledge/what-is-carbon-credit

Efficiency of Adaptive Temperature-Based Replica Exchange for Sampling Large-Scale Protein Conformational Transitions.

PubMed

Zhang, Weihong; Chen, Jianhan

2013-06-11

Temperature-based replica exchange (RE) is now considered a principal technique for enhanced sampling of protein conformations. It is also recognized that existence of sharp cooperative transitions (such as protein folding/unfolding) can lead to temperature exchange bottlenecks and significantly reduce the sampling efficiency. Here, we revisit two adaptive temperature-based RE protocols, namely, exchange equalization (EE) and current maximization (CM), that were previously examined using atomistic simulations (Lee and Olson, J. Chem. Physics2011, 134, 24111). Both protocols aim to overcome exchange bottlenecks by adaptively adjusting the simulation temperatures, either to achieve uniform exchange rates (in EE) or to maximize temperature diffusion (CM). By designing a realistic yet computationally tractable coarse-grained protein model, one can sample many reversible folding/unfolding transitions using conventional constant temperature molecular dynamics (MD), standard REMD, EE-REMD, and CM-REMD. This allows rigorous evaluation of the sampling efficiency, by directly comparing the rates of folding/unfolding transitions and convergence of various thermodynamic properties of interest. The results demonstrate that both EE and CM can indeed enhance temperature diffusion compared to standard RE, by ∼3- and over 10-fold, respectively. Surprisingly, the rates of reversible folding/unfolding transitions are similar in all three RE protocols. The convergence rates of several key thermodynamic properties, including the folding stability and various 1D and 2D free energy surfaces, are also similar. Therefore, the efficiency of RE protocols does not appear to be limited by temperature diffusion, but by the inherent rates of spontaneous large-scale conformational rearrangements. This is particularly true considering that virtually all RE simulations of proteins in practice involve exchange attempt frequencies (∼ps(-1)) that are several orders of magnitude faster than the slowest protein motions (∼μs(-1)). Our results also suggest that the efficiency of RE will not likely be improved by other protocols that aim to accelerate exchange or temperature diffusion. Instead, protocols with some types of guided tempering will likely be necessary to drive faster large-scale conformational transitions.

Physiological rules for the heart, lungs and other pressure-based organs

PubMed Central

Camilleri, Liberato; Manché, Alexander; Gatt, Ruben; Gauci, Marilyn; Camilleri-Podesta, Marie-Therese; Grima, Joseph N.; Chetcuti, Stanley

2017-01-01

Background The adherence of the heart to physical laws, such as Laplace’s Law, may act as a measure of the organ’s relative efficiency. Allometric relationships were investigated to assess the heart’s efficiency concerning end-diastolic and end-systolic volumes, cardiac pressurization energy, cardiac output and mass. Methods Data to generate allometric relationships was obtained using a literature search, identifying heart and lung data across different mammalian and bird species. Statistical analysis was carried out using ordinary least squares (OLS) estimation. Results Near isometric relationships exist between body mass and seven parameters indicating no “efficiency of size” with scaling of the heart, and size-matching of the heart to the lungs and whole body. Even though there was equal efficiency in pressurization energy generation, cardiac output was maximally efficient in small mammals <10 kg and birds; the human heart reached only 71% efficiency. This loss in cardiac efficiency with increasing body mass can be explained by the aortic cross-section that scales following the three-quarter allometry law, compared to end-systolic and end-diastolic volumes that scale isometrically. The heart is therefore throttled by a relatively small aorta at large body size. Conclusions Mammalian and avian hearts operate at similar efficiencies, demonstrating a high degree of symmorphosis, however cardiac output efficiency decreases in larger animals due to a relatively negative aortic cross-section allometry. This work has a myriad of potential applications including explaining cardiac dysfunction in athletes, patient-prosthesis mismatch in aortic valve replacement and why heavy exercise is associated with a worse prognosis than mild or moderate exercise. PMID:29268387

Industrial biomanufacturing: The future of chemical production.

PubMed

Clomburg, James M; Crumbley, Anna M; Gonzalez, Ramon

2017-01-06

The current model for industrial chemical manufacturing employs large-scale megafacilities that benefit from economies of unit scale. However, this strategy faces environmental, geographical, political, and economic challenges associated with energy and manufacturing demands. We review how exploiting biological processes for manufacturing (i.e., industrial biomanufacturing) addresses these concerns while also supporting and benefiting from economies of unit number. Key to this approach is the inherent small scale and capital efficiency of bioprocesses and the ability of engineered biocatalysts to produce designer products at high carbon and energy efficiency with adjustable output, at high selectivity, and under mild process conditions. The biological conversion of single-carbon compounds represents a test bed to establish this paradigm, enabling rapid, mobile, and widespread deployment, access to remote and distributed resources, and adaptation to new and changing markets. Copyright © 2017, American Association for the Advancement of Science.

An Inexpensive Aqueous Flow Battery for Large-Scale Electrical Energy Storage Based on Water-Soluble Organic Redox Couples

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yang, B; Hoober-Burkhardt, L; Wang, F

We introduce a novel Organic Redox Flow Battery (ORBAT), for Meeting the demanding requirements of cost, eco-friendliness, and durability for large-scale energy storage. ORBAT employs two different water-soluble organic redox couples on the positive and negative side of a flow battery. Redox couples such as quinones are particularly attractive for this application. No precious metal catalyst is needed because of the fast proton-coupled electron transfer processes. Furthermore, in acid media, the quinones exhibit good chemical stability. These properties render quinone-based redox couples very attractive for high-efficiency metal-free rechargeable batteries. We demonstrate the rechargeability of ORBAT with anthraquinone-2-sulfonic acid or anthraquinone-2,6-disulfonicmore » acid on the negative side, and 1,2-dihydrobenzoquinone- 3,5-disulfonic acid on the positive side. The ORBAT cell uses a membrane-electrode assembly configuration similar to that used in polymer electrolyte fuel cells. Such a battery can be charged and discharged multiple times at high faradaic efficiency without any noticeable degradation of performance. We show that solubility and mass transport properties of the reactants and products are paramount to achieving high current densities and high efficiency. The ORBAT configuration presents a unique opportunity for developing an inexpensive and sustainable metal-free rechargeable battery for large-scale electrical energy storage. (C) The Author(s) 2014. Published by ECS. This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 License (CC BY, http://creativecommons.orgilicenses/by/4.0/), which permits unrestricted reuse of the work in any medium, provided the original work is properly cited. All rights reserved.« less

A socio-hydrologic model of coupled water-agriculture dynamics with emphasis on farm size.

NASA Astrophysics Data System (ADS)

Brugger, D. R.; Maneta, M. P.

2015-12-01

Agricultural land cover dynamics in the U.S. are dominated by two trends: 1) total agricultural land is decreasing and 2) average farm size is increasing. These trends have important implications for the future of water resources because 1) growing more food on less land is due in large part to increased groundwater withdrawal and 2) larger farms can better afford both more efficient irrigation and more groundwater access. However, these large-scale trends are due to individual farm operators responding to many factors including climate, economics, and policy. It is therefore difficult to incorporate the trends into watershed-scale hydrologic models. Traditional scenario-based approaches are valuable for many applications, but there is typically no feedback between the hydrologic model and the agricultural dynamics and so limited insight is gained into the how agriculture co-evolves with water resources. We present a socio-hydrologic model that couples simplified hydrologic and agricultural economic dynamics, accounting for many factors that depend on farm size such as irrigation efficiency and returns to scale. We introduce an "economic memory" (EM) state variable that is driven by agricultural revenue and affects whether farms are sold when land market values exceed expected returns from agriculture. The model uses a Generalized Mixture Model of Gaussians to approximate the distribution of farm sizes in a study area, effectively lumping farms into "small," "medium," and "large" groups that have independent parameterizations. We apply the model in a semi-arid watershed in the upper Columbia River Basin, calibrating to data on streamflow, total agricultural land cover, and farm size distribution. The model is used to investigate the sensitivity of the coupled system to various hydrologic and economic scenarios such as increasing market value of land, reduced surface water availability, and increased irrigation efficiency in small farms.

Large-Scale Test of Dynamic Correlation Processors: Implications for Correlation-Based Seismic Pipelines

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dodge, D. A.; Harris, D. B.

Correlation detectors are of considerable interest to the seismic monitoring communities because they offer reduced detection thresholds and combine detection, location and identification functions into a single operation. They appear to be ideal for applications requiring screening of frequent repeating events. However, questions remain about how broadly empirical correlation methods are applicable. We describe the effectiveness of banks of correlation detectors in a system that combines traditional power detectors with correlation detectors in terms of efficiency, which we define to be the fraction of events detected by the correlators. This paper elaborates and extends the concept of a dynamic correlationmore » detection framework – a system which autonomously creates correlation detectors from event waveforms detected by power detectors; and reports observed performance on a network of arrays in terms of efficiency. We performed a large scale test of dynamic correlation processors on an 11 terabyte global dataset using 25 arrays in the single frequency band 1-3 Hz. The system found over 3.2 million unique signals and produced 459,747 screened detections. A very satisfying result is that, on average, efficiency grows with time and, after nearly 16 years of operation, exceeds 47% for events observed over all distance ranges and approaches 70% for near regional and 90% for local events. This observation suggests that future pipeline architectures should make extensive use of correlation detectors, principally for decluttering observations of local and near-regional events. Our results also suggest that future operations based on correlation detection will require commodity large-scale computing infrastructure, since the numbers of correlators in an autonomous system can grow into the hundreds of thousands.« less

Large-Scale Test of Dynamic Correlation Processors: Implications for Correlation-Based Seismic Pipelines

DOE PAGES

Dodge, D. A.; Harris, D. B.

2016-03-15

Correlation detectors are of considerable interest to the seismic monitoring communities because they offer reduced detection thresholds and combine detection, location and identification functions into a single operation. They appear to be ideal for applications requiring screening of frequent repeating events. However, questions remain about how broadly empirical correlation methods are applicable. We describe the effectiveness of banks of correlation detectors in a system that combines traditional power detectors with correlation detectors in terms of efficiency, which we define to be the fraction of events detected by the correlators. This paper elaborates and extends the concept of a dynamic correlationmore » detection framework – a system which autonomously creates correlation detectors from event waveforms detected by power detectors; and reports observed performance on a network of arrays in terms of efficiency. We performed a large scale test of dynamic correlation processors on an 11 terabyte global dataset using 25 arrays in the single frequency band 1-3 Hz. The system found over 3.2 million unique signals and produced 459,747 screened detections. A very satisfying result is that, on average, efficiency grows with time and, after nearly 16 years of operation, exceeds 47% for events observed over all distance ranges and approaches 70% for near regional and 90% for local events. This observation suggests that future pipeline architectures should make extensive use of correlation detectors, principally for decluttering observations of local and near-regional events. Our results also suggest that future operations based on correlation detection will require commodity large-scale computing infrastructure, since the numbers of correlators in an autonomous system can grow into the hundreds of thousands.« less

Stability and stabilisation of a class of networked dynamic systems

NASA Astrophysics Data System (ADS)

Liu, H. B.; Wang, D. Q.

2018-04-01

We investigate the stability and stabilisation of a linear time invariant networked heterogeneous system with arbitrarily connected subsystems. A new linear matrix inequality based sufficient and necessary condition for the stability is derived, based on which the stabilisation is provided. The obtained conditions efficiently utilise the block-diagonal characteristic of system parameter matrices and the sparseness of subsystem connection matrix. Moreover, a sufficient condition only dependent on each individual subsystem is also presented for the stabilisation of the networked systems with a large scale. Numerical simulations show that these conditions are computationally valid in the analysis and synthesis of a large-scale networked system.

An adaptive response surface method for crashworthiness optimization

NASA Astrophysics Data System (ADS)

Shi, Lei; Yang, Ren-Jye; Zhu, Ping

2013-11-01

Response surface-based design optimization has been commonly used for optimizing large-scale design problems in the automotive industry. However, most response surface models are built by a limited number of design points without considering data uncertainty. In addition, the selection of a response surface in the literature is often arbitrary. This article uses a Bayesian metric to systematically select the best available response surface among several candidates in a library while considering data uncertainty. An adaptive, efficient response surface strategy, which minimizes the number of computationally intensive simulations, was developed for design optimization of large-scale complex problems. This methodology was demonstrated by a crashworthiness optimization example.

Gossip-Based Broadcast

NASA Astrophysics Data System (ADS)

Leitão, João; Pereira, José; Rodrigues, Luís

Gossip, or epidemic, protocols have emerged as a powerful strategy to implement highly scalable and resilient reliable broadcast primitives on large scale peer-to-peer networks. Epidemic protocols are scalable because they distribute the load among all nodes in the system and resilient because they have an intrinsic level of redundancy that masks node and network failures. This chapter provides an introduction to gossip-based broadcast on large-scale unstructured peer-to-peer overlay networks: it surveys the main results in the field, discusses techniques to build and maintain the overlays that support efficient dissemination strategies, and provides an in-depth discussion and experimental evaluation of two concrete protocols, named HyParView and Plumtree.

Safe gas handling and system design for the large scale production of amorphous silicon based solar cells

NASA Astrophysics Data System (ADS)

Fortmann, C. M.; Farley, M. V.; Smoot, M. A.; Fieselmann, B. F.

1988-07-01

Solarex is one of the leaders in amorphous silicon based photovoltaic production and research. The large scale production environment presents unique safety concerns related to the quantity of dangerous materials as well as the number of personnel handling these materials. The safety measures explored by this work include gas detection systems, training, and failure resistant gas handling systems. Our experiences with flow restricting orifices in the CGA connections and the use of steel cylinders is reviewed. The hazards and efficiency of wet scrubbers for silane exhausts are examined. We have found it to be useful to provide the scrubbler with temperature alarms.

Efficient Generation of an Array of Single Silicon-Vacancy Defects in Silicon Carbide

NASA Astrophysics Data System (ADS)

Wang, Junfeng; Zhou, Yu; Zhang, Xiaoming; Liu, Fucai; Li, Yan; Li, Ke; Liu, Zheng; Wang, Guanzhong; Gao, Weibo

2017-06-01

Color centers in silicon carbide have increasingly attracted attention in recent years owing to their excellent properties such as single-photon emission, good photostability, and long spin-coherence time even at room temperature. As compared to diamond, which is widely used for hosting nitrogen-vacancy centers, silicon carbide has an advantage in terms of large-scale, high-quality, and low-cost growth, as well as an advanced fabrication technique in optoelectronics, leading to prospects for large-scale quantum engineering. In this paper, we report an experimental demonstration of the generation of a single-photon-emitter array through ion implantation. VSi defects are generated in predetermined locations with high generation efficiency (approximately 19 % ±4 % ). The single emitter probability reaches approximately 34 % ±4 % when the ion-implantation dose is properly set. This method serves as a critical step in integrating single VSi defect emitters with photonic structures, which, in turn, can improve the emission and collection efficiency of VSi defects when they are used in a spin photonic quantum network. On the other hand, the defects are shallow, and they are generated about 40 nm below the surface which can serve as a critical resource in quantum-sensing applications.

High-Performance Carbon Dioxide Electrocatalytic Reduction by Easily Fabricated Large-Scale Silver Nanowire Arrays.

PubMed

Luan, Chuhao; Shao, Yang; Lu, Qi; Gao, Shenghan; Huang, Kai; Wu, Hui; Yao, Kefu

2018-05-30

An efficient and selective catalyst is in urgent need for carbon dioxide electroreduction and silver is one of the promising candidates with affordable costs. Here we fabricated large-scale vertically standing Ag nanowire arrays with high crystallinity and electrical conductivity as carbon dioxide electroreduction catalysts by a simple nanomolding method that was usually considered not feasible for metallic crystalline materials. A great enhancement of current densities and selectivity for CO at moderate potentials was achieved. The current density for CO ( j co ) of Ag nanowire array with 200 nm in diameter was more than 2500 times larger than that of Ag foil at an overpotential of 0.49 V with an efficiency over 90%. The origin of enhanced performances are attributed to greatly increased electrochemically active surface area (ECSA) and higher intrinsic activity compared to those of polycrystalline Ag foil. More low-coordinated sites on the nanowires which can stabilize the CO 2 intermediate better are responsible for the high intrinsic activity. In addition, the impact of surface morphology that induces limited mass transportation on reaction selectivity and efficiency of nanowire arrays with different diameters was also discussed.

High-efficiency Agrobacterium-mediated transformation of Norway spruce (Picea abies) and loblolly pine (Pinus taeda)

NASA Technical Reports Server (NTRS)

Wenck, A. R.; Quinn, M.; Whetten, R. W.; Pullman, G.; Sederoff, R.; Brown, C. S. (Principal Investigator)

1999-01-01

Agrobacterium-mediated gene transfer is the method of choice for many plant biotechnology laboratories; however, large-scale use of this organism in conifer transformation has been limited by difficult propagation of explant material, selection efficiencies and low transformation frequency. We have analyzed co-cultivation conditions and different disarmed strains of Agrobacterium to improve transformation. Additional copies of virulence genes were added to three common disarmed strains. These extra virulence genes included either a constitutively active virG or extra copies of virG and virB, both from pTiBo542. In experiments with Norway spruce, we increased transformation efficiencies 1000-fold from initial experiments where little or no transient expression was detected. Over 100 transformed lines expressing the marker gene beta-glucuronidase (GUS) were generated from rapidly dividing embryogenic suspension-cultured cells co-cultivated with Agrobacterium. GUS activity was used to monitor transient expression and to further test lines selected on kanamycin-containing medium. In loblolly pine, transient expression increased 10-fold utilizing modified Agrobacterium strains. Agrobacterium-mediated gene transfer is a useful technique for large-scale generation of transgenic Norway spruce and may prove useful for other conifer species.

TopicLens: Efficient Multi-Level Visual Topic Exploration of Large-Scale Document Collections.

PubMed

Kim, Minjeong; Kang, Kyeongpil; Park, Deokgun; Choo, Jaegul; Elmqvist, Niklas

2017-01-01

Topic modeling, which reveals underlying topics of a document corpus, has been actively adopted in visual analytics for large-scale document collections. However, due to its significant processing time and non-interactive nature, topic modeling has so far not been tightly integrated into a visual analytics workflow. Instead, most such systems are limited to utilizing a fixed, initial set of topics. Motivated by this gap in the literature, we propose a novel interaction technique called TopicLens that allows a user to dynamically explore data through a lens interface where topic modeling and the corresponding 2D embedding are efficiently computed on the fly. To support this interaction in real time while maintaining view consistency, we propose a novel efficient topic modeling method and a semi-supervised 2D embedding algorithm. Our work is based on improving state-of-the-art methods such as nonnegative matrix factorization and t-distributed stochastic neighbor embedding. Furthermore, we have built a web-based visual analytics system integrated with TopicLens. We use this system to measure the performance and the visualization quality of our proposed methods. We provide several scenarios showcasing the capability of TopicLens using real-world datasets.

Supporting Regularized Logistic Regression Privately and Efficiently.

PubMed

Li, Wenfa; Liu, Hongzhe; Yang, Peng; Xie, Wei

2016-01-01

As one of the most popular statistical and machine learning models, logistic regression with regularization has found wide adoption in biomedicine, social sciences, information technology, and so on. These domains often involve data of human subjects that are contingent upon strict privacy regulations. Concerns over data privacy make it increasingly difficult to coordinate and conduct large-scale collaborative studies, which typically rely on cross-institution data sharing and joint analysis. Our work here focuses on safeguarding regularized logistic regression, a widely-used statistical model while at the same time has not been investigated from a data security and privacy perspective. We consider a common use scenario of multi-institution collaborative studies, such as in the form of research consortia or networks as widely seen in genetics, epidemiology, social sciences, etc. To make our privacy-enhancing solution practical, we demonstrate a non-conventional and computationally efficient method leveraging distributing computing and strong cryptography to provide comprehensive protection over individual-level and summary data. Extensive empirical evaluations on several studies validate the privacy guarantee, efficiency and scalability of our proposal. We also discuss the practical implications of our solution for large-scale studies and applications from various disciplines, including genetic and biomedical studies, smart grid, network analysis, etc.

Supporting Regularized Logistic Regression Privately and Efficiently

PubMed Central

Li, Wenfa; Liu, Hongzhe; Yang, Peng; Xie, Wei

2016-01-01

As one of the most popular statistical and machine learning models, logistic regression with regularization has found wide adoption in biomedicine, social sciences, information technology, and so on. These domains often involve data of human subjects that are contingent upon strict privacy regulations. Concerns over data privacy make it increasingly difficult to coordinate and conduct large-scale collaborative studies, which typically rely on cross-institution data sharing and joint analysis. Our work here focuses on safeguarding regularized logistic regression, a widely-used statistical model while at the same time has not been investigated from a data security and privacy perspective. We consider a common use scenario of multi-institution collaborative studies, such as in the form of research consortia or networks as widely seen in genetics, epidemiology, social sciences, etc. To make our privacy-enhancing solution practical, we demonstrate a non-conventional and computationally efficient method leveraging distributing computing and strong cryptography to provide comprehensive protection over individual-level and summary data. Extensive empirical evaluations on several studies validate the privacy guarantee, efficiency and scalability of our proposal. We also discuss the practical implications of our solution for large-scale studies and applications from various disciplines, including genetic and biomedical studies, smart grid, network analysis, etc. PMID:27271738

Can cooperative behaviors promote evacuation efficiency?

NASA Astrophysics Data System (ADS)

Cheng, Yuan; Zheng, Xiaoping

2018-02-01

This study aims to get insight into the question whether cooperative behaviors can promote the evacuation efficiency during an evacuation process. In this work, cooperative behaviors and evacuation efficiency have been examined in detail by using a cellular automata model with behavioral extension. The simulation results show that moderate cooperative behaviors can result in the highest evacuation efficiency. It is found that in a mixture of cooperative and competitive individuals, more cooperative people will lead to relatively high evacuation efficiency, and the larger subgroup will play a leading role. This work can also provide some new insights for the study of cooperative behaviors and evacuation efficiency which can be a scientific decision-making basis for emergency response involving large-scale crowd evacuation in emergencies.

Review of status developments of high-efficiency crystalline silicon solar cells

NASA Astrophysics Data System (ADS)

Liu, Jingjing; Yao, Yao; Xiao, Shaoqing; Gu, Xiaofeng

2018-03-01

In order to further improve cell efficiency and reduce cost in achieving grid parity, a large number of PV manufacturing companies, universities and research institutes have been devoted to a variety of low-cost and high-efficiency crystalline Si solar cells. In this article, the cell structures, characteristics and efficiency progresses of several types of high-efficiency crystalline Si solar cells that have been in small scale production or are promising in mass production are presented, including passivated emitter rear cell, tunnel oxide passivated contact solar cell, interdigitated back contact cell, heterojunction with intrinsic thin-layer cell, and heterojunction solar cells with interdigitated back contacts. Both the industrialization status and future development trend of high-efficiency crystalline silicon solar cells are also pinpointed.

Development of Residential Prototype Building Models and Analysis System for Large-Scale Energy Efficiency Studies Using EnergyPlus

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mendon, Vrushali V.; Taylor, Zachary T.

ABSTRACT: Recent advances in residential building energy efficiency and codes have resulted in increased interest in detailed residential building energy models using the latest energy simulation software. One of the challenges of developing residential building models to characterize new residential building stock is to allow for flexibility to address variability in house features like geometry, configuration, HVAC systems etc. Researchers solved this problem in a novel way by creating a simulation structure capable of creating fully-functional EnergyPlus batch runs using a completely scalable residential EnergyPlus template system. This system was used to create a set of thirty-two residential prototype buildingmore » models covering single- and multifamily buildings, four common foundation types and four common heating system types found in the United States (US). A weighting scheme with detailed state-wise and national weighting factors was designed to supplement the residential prototype models. The complete set is designed to represent a majority of new residential construction stock. The entire structure consists of a system of utility programs developed around the core EnergyPlus simulation engine to automate the creation and management of large-scale simulation studies with minimal human effort. The simulation structure and the residential prototype building models have been used for numerous large-scale studies, one of which is briefly discussed in this paper.« less

Research on precision grinding technology of large scale and ultra thin optics

NASA Astrophysics Data System (ADS)

Zhou, Lian; Wei, Qiancai; Li, Jie; Chen, Xianhua; Zhang, Qinghua

2018-03-01

The flatness and parallelism error of large scale and ultra thin optics have an important influence on the subsequent polishing efficiency and accuracy. In order to realize the high precision grinding of those ductile elements, the low deformation vacuum chuck was designed first, which was used for clamping the optics with high supporting rigidity in the full aperture. Then the optics was planar grinded under vacuum adsorption. After machining, the vacuum system was turned off. The form error of optics was on-machine measured using displacement sensor after elastic restitution. The flatness would be convergenced with high accuracy by compensation machining, whose trajectories were integrated with the measurement result. For purpose of getting high parallelism, the optics was turned over and compensation grinded using the form error of vacuum chuck. Finally, the grinding experiment of large scale and ultra thin fused silica optics with aperture of 430mm×430mm×10mm was performed. The best P-V flatness of optics was below 3 μm, and parallelism was below 3 ″. This machining technique has applied in batch grinding of large scale and ultra thin optics.

VisIRR: A Visual Analytics System for Information Retrieval and Recommendation for Large-Scale Document Data

DOE Office of Scientific and Technical Information (OSTI.GOV)

Choo, Jaegul; Kim, Hannah; Clarkson, Edward

In this paper, we present an interactive visual information retrieval and recommendation system, called VisIRR, for large-scale document discovery. VisIRR effectively combines the paradigms of (1) a passive pull through query processes for retrieval and (2) an active push that recommends items of potential interest to users based on their preferences. Equipped with an efficient dynamic query interface against a large-scale corpus, VisIRR organizes the retrieved documents into high-level topics and visualizes them in a 2D space, representing the relationships among the topics along with their keyword summary. In addition, based on interactive personalized preference feedback with regard to documents,more » VisIRR provides document recommendations from the entire corpus, which are beyond the retrieved sets. Such recommended documents are visualized in the same space as the retrieved documents, so that users can seamlessly analyze both existing and newly recommended ones. This article presents novel computational methods, which make these integrated representations and fast interactions possible for a large-scale document corpus. We illustrate how the system works by providing detailed usage scenarios. Finally, we present preliminary user study results for evaluating the effectiveness of the system.« less

VisIRR: A Visual Analytics System for Information Retrieval and Recommendation for Large-Scale Document Data

DOE PAGES

Choo, Jaegul; Kim, Hannah; Clarkson, Edward; ...

2018-01-31

In this paper, we present an interactive visual information retrieval and recommendation system, called VisIRR, for large-scale document discovery. VisIRR effectively combines the paradigms of (1) a passive pull through query processes for retrieval and (2) an active push that recommends items of potential interest to users based on their preferences. Equipped with an efficient dynamic query interface against a large-scale corpus, VisIRR organizes the retrieved documents into high-level topics and visualizes them in a 2D space, representing the relationships among the topics along with their keyword summary. In addition, based on interactive personalized preference feedback with regard to documents,more » VisIRR provides document recommendations from the entire corpus, which are beyond the retrieved sets. Such recommended documents are visualized in the same space as the retrieved documents, so that users can seamlessly analyze both existing and newly recommended ones. This article presents novel computational methods, which make these integrated representations and fast interactions possible for a large-scale document corpus. We illustrate how the system works by providing detailed usage scenarios. Finally, we present preliminary user study results for evaluating the effectiveness of the system.« less

A Matter of Time: Faster Percolator Analysis via Efficient SVM Learning for Large-Scale Proteomics.

PubMed

Halloran, John T; Rocke, David M

2018-05-04

Percolator is an important tool for greatly improving the results of a database search and subsequent downstream analysis. Using support vector machines (SVMs), Percolator recalibrates peptide-spectrum matches based on the learned decision boundary between targets and decoys. To improve analysis time for large-scale data sets, we update Percolator's SVM learning engine through software and algorithmic optimizations rather than heuristic approaches that necessitate the careful study of their impact on learned parameters across different search settings and data sets. We show that by optimizing Percolator's original learning algorithm, l 2 -SVM-MFN, large-scale SVM learning requires nearly only a third of the original runtime. Furthermore, we show that by employing the widely used Trust Region Newton (TRON) algorithm instead of l 2 -SVM-MFN, large-scale Percolator SVM learning is reduced to nearly only a fifth of the original runtime. Importantly, these speedups only affect the speed at which Percolator converges to a global solution and do not alter recalibration performance. The upgraded versions of both l 2 -SVM-MFN and TRON are optimized within the Percolator codebase for multithreaded and single-thread use and are available under Apache license at bitbucket.org/jthalloran/percolator_upgrade .

Highly Efficient Large-Scale Lentiviral Vector Concentration by Tandem Tangential Flow Filtration

PubMed Central

Cooper, Aaron R.; Patel, Sanjeet; Senadheera, Shantha; Plath, Kathrin; Kohn, Donald B.; Hollis, Roger P.

2014-01-01

Large-scale lentiviral vector (LV) concentration can be inefficient and time consuming, often involving multiple rounds of filtration and centrifugation. This report describes a simpler method using two tangential flow filtration (TFF) steps to concentrate liter-scale volumes of LV supernatant, achieving in excess of 2000-fold concentration in less than 3 hours with very high recovery (>97%). Large volumes of LV supernatant can be produced easily through the use of multi-layer flasks, each having 1720 cm2 surface area and producing ~560 mL of supernatant per flask. Combining the use of such flasks and TFF greatly simplifies large-scale production of LV. As a demonstration, the method is used to produce a very high titer LV (>1010 TU/mL) and transduce primary human CD34+ hematopoietic stem/progenitor cells at high final vector concentrations with no overt toxicity. A complex LV (STEMCCA) for induced pluripotent stem cell generation is also concentrated from low initial titer and used to transduce and reprogram primary human fibroblasts with no overt toxicity. Additionally, a generalized and simple multiplexed real- time PCR assay is described for lentiviral vector titer and copy number determination. PMID:21784103

Approximate Computing Techniques for Iterative Graph Algorithms

DOE Office of Scientific and Technical Information (OSTI.GOV)

Panyala, Ajay R.; Subasi, Omer; Halappanavar, Mahantesh

Approximate computing enables processing of large-scale graphs by trading off quality for performance. Approximate computing techniques have become critical not only due to the emergence of parallel architectures but also the availability of large scale datasets enabling data-driven discovery. Using two prototypical graph algorithms, PageRank and community detection, we present several approximate computing heuristics to scale the performance with minimal loss of accuracy. We present several heuristics including loop perforation, data caching, incomplete graph coloring and synchronization, and evaluate their efficiency. We demonstrate performance improvements of up to 83% for PageRank and up to 450x for community detection, with lowmore » impact of accuracy for both the algorithms. We expect the proposed approximate techniques will enable scalable graph analytics on data of importance to several applications in science and their subsequent adoption to scale similar graph algorithms.« less

Multiscale solvers and systematic upscaling in computational physics

NASA Astrophysics Data System (ADS)

Brandt, A.

2005-07-01

Multiscale algorithms can overcome the scale-born bottlenecks that plague most computations in physics. These algorithms employ separate processing at each scale of the physical space, combined with interscale iterative interactions, in ways which use finer scales very sparingly. Having been developed first and well known as multigrid solvers for partial differential equations, highly efficient multiscale techniques have more recently been developed for many other types of computational tasks, including: inverse PDE problems; highly indefinite (e.g., standing wave) equations; Dirac equations in disordered gauge fields; fast computation and updating of large determinants (as needed in QCD); fast integral transforms; integral equations; astrophysics; molecular dynamics of macromolecules and fluids; many-atom electronic structures; global and discrete-state optimization; practical graph problems; image segmentation and recognition; tomography (medical imaging); fast Monte-Carlo sampling in statistical physics; and general, systematic methods of upscaling (accurate numerical derivation of large-scale equations from microscopic laws).

Protection against heavy metal toxicity by mucous and scales in fish

DOE Office of Scientific and Technical Information (OSTI.GOV)

Coello, W.F.; Khan, M.A.Q.

1995-12-31

Fingerlings of three freshwater fish species showed differences in susceptibility to lethality of 250 mg/L lead suspension or lead nitrate solution in water. Among these the large mouth bass Micropterus salmoides seemed to be more tolerant than green sunfish Lepomis cyanellus and goldfish Carassius auratus. Mucous from large mouth bass, when added to jars containing lead, lowered the toxicity of lead to sunfish and goldfish. Adding scales, especially if these were pretreated with an alkaline solution of cysteine and glycine, made all these species become tolerant to otherwise lethal concentrations of lead nitrate. The scales and mucous together buffered themore » acidity of lead nitrate and mercuric nitrate solution and sequestered hydrogen ions and lead and mercury from water and then settled to the bottom of jars. Scales of younger fingerling were more efficient than those of older ones.« less

Some issues related to the novel spectral acceleration method for the fast computation of radiation/scattering from one-dimensional extremely large scale quasi-planar structures

NASA Astrophysics Data System (ADS)

Torrungrueng, Danai; Johnson, Joel T.; Chou, Hsi-Tseng

2002-03-01

The novel spectral acceleration (NSA) algorithm has been shown to produce an $[\\mathcal{O}]$(Ntot) efficient iterative method of moments for the computation of radiation/scattering from both one-dimensional (1-D) and two-dimensional large-scale quasi-planar structures, where Ntot is the total number of unknowns to be solved. This method accelerates the matrix-vector multiplication in an iterative method of moments solution and divides contributions between points into ``strong'' (exact matrix elements) and ``weak'' (NSA algorithm) regions. The NSA method is based on a spectral representation of the electromagnetic Green's function and appropriate contour deformation, resulting in a fast multipole-like formulation in which contributions from large numbers of points to a single point are evaluated simultaneously. In the standard NSA algorithm the NSA parameters are derived on the basis of the assumption that the outermost possible saddle point, φs,max, along the real axis in the complex angular domain is small. For given height variations of quasi-planar structures, this assumption can be satisfied by adjusting the size of the strong region Ls. However, for quasi-planar structures with large height variations, the adjusted size of the strong region is typically large, resulting in significant increases in computational time for the computation of the strong-region contribution and degrading overall efficiency of the NSA algorithm. In addition, for the case of extremely large scale structures, studies based on the physical optics approximation and a flat surface assumption show that the given NSA parameters in the standard NSA algorithm may yield inaccurate results. In this paper, analytical formulas associated with the NSA parameters for an arbitrary value of φs,max are presented, resulting in more flexibility in selecting Ls to compromise between the computation of the contributions of the strong and weak regions. In addition, a ``multilevel'' algorithm, decomposing 1-D extremely large scale quasi-planar structures into more than one weak region and appropriately choosing the NSA parameters for each weak region, is incorporated into the original NSA method to improve its accuracy.

Production technology for high efficiency ion implanted solar cells

NASA Technical Reports Server (NTRS)

Kirkpatrick, A. R.; Minnucci, J. A.; Greenwald, A. C.; Josephs, R. H.

1978-01-01

Ion implantation is being developed for high volume automated production of silicon solar cells. An implanter designed for solar cell processing and able to properly implant up to 300 4-inch wafers per hour is now operational. A machine to implant 180 sq m/hr of solar cell material has been designed. Implanted silicon solar cells with efficiencies exceeding 16% AM1 are now being produced and higher efficiencies are expected. Ion implantation and transient processing by pulsed electron beams are being integrated with electrostatic bonding to accomplish a simple method for large scale, low cost production of high efficiency solar cell arrays.

Production regimes in four eastern boundary current systems

NASA Technical Reports Server (NTRS)

Carr, M. E.; Kearns, E. J.

2003-01-01

High productivity (maxima 3 g C m(sup -2)day(sup -1)) of the Eastern Boundary Currents (EBCs), i.e. the California, Peru-Humboldt, Canary and Benguela Currents, is driven by a combination of local forcing and large-scale circulation. The characteristics of the deep water brought to the surface by upwelling favorable winds depend on the large-scale circulation patterns. Here we use a new hydrographic and nutrient climatology together with satellite measurements ofthe wind vector, sea-surface temperature (SST), chlorophyll concentration, and primary production modeled from ocean color to quantify the meridional and seasonal patterns of upwelling dynamics and biological response. The unprecedented combination of data sets allows us to describe objectively the variability for small regions within each current and to characterize the governing factors for biological production. The temporal and spatial environmental variability was due in most regions to large-scale circulation, alone or in combination with offshore transport (local forcing). The observed meridional and seasonal patterns of biomass and primary production were most highlycorrelated to components representing large-scale circulation. The biomass sustained by a given nutrient concentration in the Atlantic EBCs was twice as large as that of the Pacific EBCs. This apparent greater efficiency may be due toavailability of iron, physical retention, or differences in planktonic community structure.

Screening and large-scale expression of membrane proteins in mammalian cells for structural studies.

PubMed

Goehring, April; Lee, Chia-Hsueh; Wang, Kevin H; Michel, Jennifer Carlisle; Claxton, Derek P; Baconguis, Isabelle; Althoff, Thorsten; Fischer, Suzanne; Garcia, K Christopher; Gouaux, Eric

2014-11-01

Structural, biochemical and biophysical studies of eukaryotic membrane proteins are often hampered by difficulties in overexpression of the candidate molecule. Baculovirus transduction of mammalian cells (BacMam), although a powerful method to heterologously express membrane proteins, can be cumbersome for screening and expression of multiple constructs. We therefore developed plasmid Eric Gouaux (pEG) BacMam, a vector optimized for use in screening assays, as well as for efficient production of baculovirus and robust expression of the target protein. In this protocol, we show how to use small-scale transient transfection and fluorescence-detection size-exclusion chromatography (FSEC) experiments using a GFP-His8-tagged candidate protein to screen for monodispersity and expression level. Once promising candidates are identified, we describe how to generate baculovirus, transduce HEK293S GnTI(-) (N-acetylglucosaminyltransferase I-negative) cells in suspension culture and overexpress the candidate protein. We have used these methods to prepare pure samples of chicken acid-sensing ion channel 1a (cASIC1) and Caenorhabditis elegans glutamate-gated chloride channel (GluCl) for X-ray crystallography, demonstrating how to rapidly and efficiently screen hundreds of constructs and accomplish large-scale expression in 4-6 weeks.

Screening and large-scale expression of membrane proteins in mammalian cells for structural studies

PubMed Central

Goehring, April; Lee, Chia-Hsueh; Wang, Kevin H.; Michel, Jennifer Carlisle; Claxton, Derek P.; Baconguis, Isabelle; Althoff, Thorsten; Fischer, Suzanne; Garcia, K. Christopher; Gouaux, Eric

2014-01-01

Structural, biochemical and biophysical studies of eukaryotic membrane proteins are often hampered by difficulties in over-expression of the candidate molecule. Baculovirus transduction of mammalian cells (BacMam), although a powerful method to heterologously express membrane proteins, can be cumbersome for screening and expression of multiple constructs. We therefore developed plasmid Eric Gouaux (pEG) BacMam, a vector optimized for use in screening assays, as well as for efficient production of baculovirus and robust expression of the target protein. In this protocol we show how to use small-scale transient transfection and fluorescence-detection, size-exclusion chromatography (FSEC) experiments using a GFP-His8 tagged candidate protein to screen for monodispersity and expression level. Once promising candidates are identified, we describe how to generate baculovirus, transduce HEK293S GnTI− (N-acetylglucosaminyltransferase I-negative) cells in suspension culture, and over-express the candidate protein. We have used these methods to prepare pure samples of chicken acid-sensing ion channel 1a (cASIC1) and Caenorhabditis elegans glutamate-gated chloride channel (GluCl), for X-ray crystallography, demonstrating how to rapidly and efficiently screen hundreds of constructs and accomplish large-scale expression in 4-6 weeks. PMID:25299155

Strategic Energy Planning (Area 1) Consultants Reports to Citizen Potawatomi Nation Federally Recognized Indian Tribe

DOE Office of Scientific and Technical Information (OSTI.GOV)

Smith, Marvin; Bose, James; Beier, Richard

2004-12-01

The assets that Citizen Potawatomi Nation holds were evaluated to help define the strengths and weaknesses to be used in pursuing economic prosperity. With this baseline assessment, a Planning Team will create a vision for the tribe to integrate into long-term energy and business strategies. Identification of energy efficiency devices, systems and technologies was made, and an estimation of cost benefits of the more promising ideas is submitted for possible inclusion into the final energy plan. Multiple energy resources and sources were identified and their attributes were assessed to determine the appropriateness of each. Methods of saving energy were evaluatedmore » and reported on and potential revenue-generating sources that specifically fit the tribe were identified and reported. A primary goal is to create long-term energy strategies to explore development of tribal utility options and analyze renewable energy and energy efficiency options. Associated goals are to consider exploring energy efficiency and renewable economic development projects involving the following topics: (1) Home-scale projects may include construction of a home with energy efficiency or renewable energy features and retrofitting an existing home to add energy efficiency or renewable energy features. (2) Community-scale projects may include medium to large scale energy efficiency building construction, retrofit project, or installation of community renewable energy systems. (3) Small business development may include the creation of a tribal enterprise that would manufacture and distribute solar and wind powered equipment for ranches and farms or create a contracting business to include energy efficiency and renewable retrofits such as geothermal heat pumps. (4) Commercial-scale energy projects may include at a larger scale, the formation of a tribal utility formed to sell power to the commercial grid, or to transmit and distribute power throughout the tribal community, or hydrogen production, and propane and natural-gas distribution systems.« less

Aerodynamic flow deflector to increase large scale wind turbine power generation by 10%.

DOT National Transportation Integrated Search

2015-11-01

The innovation proposed in this paper has the potential to address both the efficiency demands of wind farm owners as well as to provide a disruptive design innovation to turbine manufacturers. The aerodynamic deflector technology was created to impr...

Engineering Education for Agricultural and Rural Development in Africa

ERIC Educational Resources Information Center

Adewumi, B. A.

2008-01-01

Agricultural Engineering has transformed agricultural practices from subsistence level to medium and large-scale production via mechanisation in the developed nations. This has reduced the labour force requirements in agriculture; increased production levels and efficiency, product shelf life and product quality; and resulted into…

Ordering Unstructured Meshes for Sparse Matrix Computations on Leading Parallel Systems

NASA Technical Reports Server (NTRS)

Oliker, Leonid; Li, Xiaoye; Heber, Gerd; Biswas, Rupak

2000-01-01

The ability of computers to solve hitherto intractable problems and simulate complex processes using mathematical models makes them an indispensable part of modern science and engineering. Computer simulations of large-scale realistic applications usually require solving a set of non-linear partial differential equations (PDES) over a finite region. For example, one thrust area in the DOE Grand Challenge projects is to design future accelerators such as the SpaHation Neutron Source (SNS). Our colleagues at SLAC need to model complex RFQ cavities with large aspect ratios. Unstructured grids are currently used to resolve the small features in a large computational domain; dynamic mesh adaptation will be added in the future for additional efficiency. The PDEs for electromagnetics are discretized by the FEM method, which leads to a generalized eigenvalue problem Kx = AMx, where K and M are the stiffness and mass matrices, and are very sparse. In a typical cavity model, the number of degrees of freedom is about one million. For such large eigenproblems, direct solution techniques quickly reach the memory limits. Instead, the most widely-used methods are Krylov subspace methods, such as Lanczos or Jacobi-Davidson. In all the Krylov-based algorithms, sparse matrix-vector multiplication (SPMV) must be performed repeatedly. Therefore, the efficiency of SPMV usually determines the eigensolver speed. SPMV is also one of the most heavily used kernels in large-scale numerical simulations.

Tradeoffs and synergies between biofuel production and large-scale solar infrastructure in deserts

NASA Astrophysics Data System (ADS)

Ravi, S.; Lobell, D. B.; Field, C. B.

2012-12-01

Solar energy installations in deserts are on the rise, fueled by technological advances and policy changes. Deserts, with a combination of high solar radiation and availability of large areas unusable for crop production are ideal locations for large scale solar installations. For efficient power generation, solar infrastructures require large amounts of water for operation (mostly for cleaning panels and dust suppression), leading to significant moisture additions to desert soil. A pertinent question is how to use the moisture inputs for sustainable agriculture/biofuel production. We investigated the water requirements for large solar infrastructures in North American deserts and explored the possibilities for integrating biofuel production with solar infrastructure. In co-located systems the possible decline in yields due to shading by solar panels may be offsetted by the benefits of periodic water addition to biofuel crops, simpler dust management and more efficient power generation in solar installations, and decreased impacts on natural habitats and scarce resources in deserts. In particular, we evaluated the potential to integrate solar infrastructure with biomass feedstocks that grow in arid and semi-arid lands (Agave Spp), which are found to produce high yields with minimal water inputs. To this end, we conducted detailed life cycle analysis for these coupled agave biofuel - solar energy systems to explore the tradeoffs and synergies, in the context of energy input-output, water use and carbon emissions.

Iterative quantization: a Procrustean approach to learning binary codes for large-scale image retrieval.

PubMed

Gong, Yunchao; Lazebnik, Svetlana; Gordo, Albert; Perronnin, Florent

2013-12-01

This paper addresses the problem of learning similarity-preserving binary codes for efficient similarity search in large-scale image collections. We formulate this problem in terms of finding a rotation of zero-centered data so as to minimize the quantization error of mapping this data to the vertices of a zero-centered binary hypercube, and propose a simple and efficient alternating minimization algorithm to accomplish this task. This algorithm, dubbed iterative quantization (ITQ), has connections to multiclass spectral clustering and to the orthogonal Procrustes problem, and it can be used both with unsupervised data embeddings such as PCA and supervised embeddings such as canonical correlation analysis (CCA). The resulting binary codes significantly outperform several other state-of-the-art methods. We also show that further performance improvements can result from transforming the data with a nonlinear kernel mapping prior to PCA or CCA. Finally, we demonstrate an application of ITQ to learning binary attributes or "classemes" on the ImageNet data set.

Efficient collective influence maximization in cascading processes with first-order transitions

PubMed Central

Pei, Sen; Teng, Xian; Shaman, Jeffrey; Morone, Flaviano; Makse, Hernán A.

2017-01-01

In many social and biological networks, the collective dynamics of the entire system can be shaped by a small set of influential units through a global cascading process, manifested by an abrupt first-order transition in dynamical behaviors. Despite its importance in applications, efficient identification of multiple influential spreaders in cascading processes still remains a challenging task for large-scale networks. Here we address this issue by exploring the collective influence in general threshold models of cascading process. Our analysis reveals that the importance of spreaders is fixed by the subcritical paths along which cascades propagate: the number of subcritical paths attached to each spreader determines its contribution to global cascades. The concept of subcritical path allows us to introduce a scalable algorithm for massively large-scale networks. Results in both synthetic random graphs and real networks show that the proposed method can achieve larger collective influence given the same number of seeds compared with other scalable heuristic approaches. PMID:28349988

Enhanced heat transfer is dependent on thickness of graphene films: the heat dissipation during boiling

PubMed Central

Ahn, Ho Seon; Kim, Jin Man; Kim, TaeJoo; Park, Su Cheong; Kim, Ji Min; Park, Youngjae; Yu, Dong In; Hwang, Kyoung Won; Jo, HangJin; Park, Hyun Sun; Kim, Hyungdae; Kim, Moo Hwan

2014-01-01

Boiling heat transfer (BHT) is a particularly efficient heat transport method because of the latent heat associated with the process. However, the efficiency of BHT decreases significantly with increasing wall temperature when the critical heat flux (CHF) is reached. Graphene has received much recent research attention for applications in thermal engineering due to its large thermal conductivity. In this study, graphene films of various thicknesses were deposited on a heated surface, and enhancements of BHT and CHF were investigated via pool-boiling experiments. In contrast to the well-known surface effects, including improved wettability and liquid spreading due to micron- and nanometer-scale structures, nanometer-scale folded edges of graphene films provided a clue of BHT improvement and only the thermal conductivity of the graphene layer could explain the dependence of the CHF on the thickness. The large thermal conductivity of the graphene films inhibited the formation of hot spots, thereby increasing the CHF. Finally, the provided empirical model could be suitable for prediction of CHF. PMID:25182076

Nonlinear model-order reduction for compressible flow solvers using the Discrete Empirical Interpolation Method

NASA Astrophysics Data System (ADS)

Fosas de Pando, Miguel; Schmid, Peter J.; Sipp, Denis

2016-11-01

Nonlinear model reduction for large-scale flows is an essential component in many fluid applications such as flow control, optimization, parameter space exploration and statistical analysis. In this article, we generalize the POD-DEIM method, introduced by Chaturantabut & Sorensen [1], to address nonlocal nonlinearities in the equations without loss of performance or efficiency. The nonlinear terms are represented by nested DEIM-approximations using multiple expansion bases based on the Proper Orthogonal Decomposition. These extensions are imperative, for example, for applications of the POD-DEIM method to large-scale compressible flows. The efficient implementation of the presented model-reduction technique follows our earlier work [2] on linearized and adjoint analyses and takes advantage of the modular structure of our compressible flow solver. The efficacy of the nonlinear model-reduction technique is demonstrated to the flow around an airfoil and its acoustic footprint. We could obtain an accurate and robust low-dimensional model that captures the main features of the full flow.

Efficient RNA drug delivery using red blood cell extracellular vesicles.

PubMed

Usman, Waqas Muhammad; Pham, Tin Chanh; Kwok, Yuk Yan; Vu, Luyen Tien; Ma, Victor; Peng, Boya; Chan, Yuen San; Wei, Likun; Chin, Siew Mei; Azad, Ajijur; He, Alex Bai-Liang; Leung, Anskar Y H; Yang, Mengsu; Shyh-Chang, Ng; Cho, William C; Shi, Jiahai; Le, Minh T N

2018-06-15

Most of the current methods for programmable RNA drug therapies are unsuitable for the clinic due to low uptake efficiency and high cytotoxicity. Extracellular vesicles (EVs) could solve these problems because they represent a natural mode of intercellular communication. However, current cellular sources for EV production are limited in availability and safety in terms of horizontal gene transfer. One potentially ideal source could be human red blood cells (RBCs). Group O-RBCs can be used as universal donors for large-scale EV production since they are readily available in blood banks and they are devoid of DNA. Here, we describe and validate a new strategy to generate large-scale amounts of RBC-derived EVs for the delivery of RNA drugs, including antisense oligonucleotides, Cas9 mRNA, and guide RNAs. RNA drug delivery with RBCEVs shows highly robust microRNA inhibition and CRISPR-Cas9 genome editing in both human cells and xenograft mouse models, with no observable cytotoxicity.

Reliable and efficient solution of genome-scale models of Metabolism and macromolecular Expression

DOE PAGES

Ma, Ding; Yang, Laurence; Fleming, Ronan M. T.; ...

2017-01-18

Currently, Constraint-Based Reconstruction and Analysis (COBRA) is the only methodology that permits integrated modeling of Metabolism and macromolecular Expression (ME) at genome-scale. Linear optimization computes steady-state flux solutions to ME models, but flux values are spread over many orders of magnitude. Data values also have greatly varying magnitudes. Furthermore, standard double-precision solvers may return inaccurate solutions or report that no solution exists. Exact simplex solvers based on rational arithmetic require a near-optimal warm start to be practical on large problems (current ME models have 70,000 constraints and variables and will grow larger). We also developed a quadrupleprecision version of ourmore » linear and nonlinear optimizer MINOS, and a solution procedure (DQQ) involving Double and Quad MINOS that achieves reliability and efficiency for ME models and other challenging problems tested here. DQQ will enable extensive use of large linear and nonlinear models in systems biology and other applications involving multiscale data.« less

On the impact of approximate computation in an analog DeSTIN architecture.

PubMed

Young, Steven; Lu, Junjie; Holleman, Jeremy; Arel, Itamar

2014-05-01

Deep machine learning (DML) holds the potential to revolutionize machine learning by automating rich feature extraction, which has become the primary bottleneck of human engineering in pattern recognition systems. However, the heavy computational burden renders DML systems implemented on conventional digital processors impractical for large-scale problems. The highly parallel computations required to implement large-scale deep learning systems are well suited to custom hardware. Analog computation has demonstrated power efficiency advantages of multiple orders of magnitude relative to digital systems while performing nonideal computations. In this paper, we investigate typical error sources introduced by analog computational elements and their impact on system-level performance in DeSTIN--a compositional deep learning architecture. These inaccuracies are evaluated on a pattern classification benchmark, clearly demonstrating the robustness of the underlying algorithm to the errors introduced by analog computational elements. A clear understanding of the impacts of nonideal computations is necessary to fully exploit the efficiency of analog circuits.

Newmark local time stepping on high-performance computing architectures

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rietmann, Max, E-mail: max.rietmann@erdw.ethz.ch; Institute of Geophysics, ETH Zurich; Grote, Marcus, E-mail: marcus.grote@unibas.ch

In multi-scale complex media, finite element meshes often require areas of local refinement, creating small elements that can dramatically reduce the global time-step for wave-propagation problems due to the CFL condition. Local time stepping (LTS) algorithms allow an explicit time-stepping scheme to adapt the time-step to the element size, allowing near-optimal time-steps everywhere in the mesh. We develop an efficient multilevel LTS-Newmark scheme and implement it in a widely used continuous finite element seismic wave-propagation package. In particular, we extend the standard LTS formulation with adaptations to continuous finite element methods that can be implemented very efficiently with very strongmore » element-size contrasts (more than 100x). Capable of running on large CPU and GPU clusters, we present both synthetic validation examples and large scale, realistic application examples to demonstrate the performance and applicability of the method and implementation on thousands of CPU cores and hundreds of GPUs.« less

A precise integration method for solving coupled vehicle-track dynamics with nonlinear wheel-rail contact

NASA Astrophysics Data System (ADS)

Zhang, J.; Gao, Q.; Tan, S. J.; Zhong, W. X.

2012-10-01

A new method is proposed as a solution for the large-scale coupled vehicle-track dynamic model with nonlinear wheel-rail contact. The vehicle is simplified as a multi-rigid-body model, and the track is treated as a three-layer beam model. In the track model, the rail is assumed to be an Euler-Bernoulli beam supported by discrete sleepers. The vehicle model and the track model are coupled using Hertzian nonlinear contact theory, and the contact forces of the vehicle subsystem and the track subsystem are approximated by the Lagrange interpolation polynomial. The response of the large-scale coupled vehicle-track model is calculated using the precise integration method. A more efficient algorithm based on the periodic property of the track is applied to calculate the exponential matrix and certain matrices related to the solution of the track subsystem. Numerical examples demonstrate the computational accuracy and efficiency of the proposed method.

Locating inefficient links in a large-scale transportation network

NASA Astrophysics Data System (ADS)

Sun, Li; Liu, Like; Xu, Zhongzhi; Jie, Yang; Wei, Dong; Wang, Pu

2015-02-01

Based on data from geographical information system (GIS) and daily commuting origin destination (OD) matrices, we estimated the distribution of traffic flow in the San Francisco road network and studied Braess's paradox in a large-scale transportation network with realistic travel demand. We measured the variation of total travel time Δ T when a road segment is closed, and found that | Δ T | follows a power-law distribution if Δ T < 0 or Δ T > 0. This implies that most roads have a negligible effect on the efficiency of the road network, while the failure of a few crucial links would result in severe travel delays, and closure of a few inefficient links would counter-intuitively reduce travel costs considerably. Generating three theoretical networks, we discovered that the heterogeneously distributed travel demand may be the origin of the observed power-law distributions of | Δ T | . Finally, a genetic algorithm was used to pinpoint inefficient link clusters in the road network. We found that closing specific road clusters would further improve the transportation efficiency.

Efficient collective influence maximization in cascading processes with first-order transitions

NASA Astrophysics Data System (ADS)

Pei, Sen; Teng, Xian; Shaman, Jeffrey; Morone, Flaviano; Makse, Hernán A.

2017-03-01

In many social and biological networks, the collective dynamics of the entire system can be shaped by a small set of influential units through a global cascading process, manifested by an abrupt first-order transition in dynamical behaviors. Despite its importance in applications, efficient identification of multiple influential spreaders in cascading processes still remains a challenging task for large-scale networks. Here we address this issue by exploring the collective influence in general threshold models of cascading process. Our analysis reveals that the importance of spreaders is fixed by the subcritical paths along which cascades propagate: the number of subcritical paths attached to each spreader determines its contribution to global cascades. The concept of subcritical path allows us to introduce a scalable algorithm for massively large-scale networks. Results in both synthetic random graphs and real networks show that the proposed method can achieve larger collective influence given the same number of seeds compared with other scalable heuristic approaches.

Feature hashing for fast image retrieval

NASA Astrophysics Data System (ADS)

Yan, Lingyu; Fu, Jiarun; Zhang, Hongxin; Yuan, Lu; Xu, Hui

2018-03-01

Currently, researches on content based image retrieval mainly focus on robust feature extraction. However, due to the exponential growth of online images, it is necessary to consider searching among large scale images, which is very timeconsuming and unscalable. Hence, we need to pay much attention to the efficiency of image retrieval. In this paper, we propose a feature hashing method for image retrieval which not only generates compact fingerprint for image representation, but also prevents huge semantic loss during the process of hashing. To generate the fingerprint, an objective function of semantic loss is constructed and minimized, which combine the influence of both the neighborhood structure of feature data and mapping error. Since the machine learning based hashing effectively preserves neighborhood structure of data, it yields visual words with strong discriminability. Furthermore, the generated binary codes leads image representation building to be of low-complexity, making it efficient and scalable to large scale databases. Experimental results show good performance of our approach.

Reliable and efficient solution of genome-scale models of Metabolism and macromolecular Expression

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ma, Ding; Yang, Laurence; Fleming, Ronan M. T.

Currently, Constraint-Based Reconstruction and Analysis (COBRA) is the only methodology that permits integrated modeling of Metabolism and macromolecular Expression (ME) at genome-scale. Linear optimization computes steady-state flux solutions to ME models, but flux values are spread over many orders of magnitude. Data values also have greatly varying magnitudes. Furthermore, standard double-precision solvers may return inaccurate solutions or report that no solution exists. Exact simplex solvers based on rational arithmetic require a near-optimal warm start to be practical on large problems (current ME models have 70,000 constraints and variables and will grow larger). We also developed a quadrupleprecision version of ourmore » linear and nonlinear optimizer MINOS, and a solution procedure (DQQ) involving Double and Quad MINOS that achieves reliability and efficiency for ME models and other challenging problems tested here. DQQ will enable extensive use of large linear and nonlinear models in systems biology and other applications involving multiscale data.« less

A Commercialization Roadmap for Carbon-Negative Energy Systems

NASA Astrophysics Data System (ADS)

Sanchez, D.

2016-12-01

The Intergovernmental Panel on Climate Change (IPCC) envisages the need for large-scale deployment of net-negative CO2 emissions technologies by mid-century to meet stringent climate mitigation goals and yield a net drawdown of atmospheric carbon. Yet there are few commercial deployments of BECCS outside of niche markets, creating uncertainty about commercialization pathways and sustainability impacts at scale. This uncertainty is exacerbated by the absence of a strong policy framework, such as high carbon prices and research coordination. Here, we propose a strategy for the potential commercial deployment of BECCS. This roadmap proceeds via three steps: 1) via capture and utilization of biogenic CO2 from existing bioenergy facilities, notably ethanol fermentation, 2) via thermochemical co-conversion of biomass and fossil fuels, particularly coal, and 3) via dedicated, large-scale BECCS. Although biochemical conversion is a proven first market for BECCS, this trajectory alone is unlikely to drive commercialization of BECCS at the gigatonne scale. In contrast to biochemical conversion, thermochemical conversion of coal and biomass enables large-scale production of fuels and electricity with a wide range of carbon intensities, process efficiencies and process scales. Aside from systems integration, primarily technical barriers are involved in large-scale biomass logistics, gasification and gas cleaning. Key uncertainties around large-scale BECCS deployment are not limited to commercialization pathways; rather, they include physical constraints on biomass cultivation or CO2 storage, as well as social barriers, including public acceptance of new technologies and conceptions of renewable and fossil energy, which co-conversion systems confound. Despite sustainability risks, this commercialization strategy presents a pathway where energy suppliers, manufacturers and governments could transition from laggards to leaders in climate change mitigation efforts.

The TeraShake Computational Platform for Large-Scale Earthquake Simulations

NASA Astrophysics Data System (ADS)

Cui, Yifeng; Olsen, Kim; Chourasia, Amit; Moore, Reagan; Maechling, Philip; Jordan, Thomas

Geoscientific and computer science researchers with the Southern California Earthquake Center (SCEC) are conducting a large-scale, physics-based, computationally demanding earthquake system science research program with the goal of developing predictive models of earthquake processes. The computational demands of this program continue to increase rapidly as these researchers seek to perform physics-based numerical simulations of earthquake processes for larger meet the needs of this research program, a multiple-institution team coordinated by SCEC has integrated several scientific codes into a numerical modeling-based research tool we call the TeraShake computational platform (TSCP). A central component in the TSCP is a highly scalable earthquake wave propagation simulation program called the TeraShake anelastic wave propagation (TS-AWP) code. In this chapter, we describe how we extended an existing, stand-alone, wellvalidated, finite-difference, anelastic wave propagation modeling code into the highly scalable and widely used TS-AWP and then integrated this code into the TeraShake computational platform that provides end-to-end (initialization to analysis) research capabilities. We also describe the techniques used to enhance the TS-AWP parallel performance on TeraGrid supercomputers, as well as the TeraShake simulations phases including input preparation, run time, data archive management, and visualization. As a result of our efforts to improve its parallel efficiency, the TS-AWP has now shown highly efficient strong scaling on over 40K processors on IBM’s BlueGene/L Watson computer. In addition, the TSCP has developed into a computational system that is useful to many members of the SCEC community for performing large-scale earthquake simulations.

Replica Exchange with Solute Tempering: Efficiency in Large Scale Systems

PubMed Central

Huang, Xuhui; Hagen, Morten; Kim, Byungchan; Friesner, Richard A.; Zhou, Ruhong; Berne, B. J.

2009-01-01

We apply the recently developed replica exchange with solute tempering (REST) to three large solvated peptide systems: an α-helix, a β-hairpin, and a TrpCage, with these peptides defined as the “central group”. We find that our original implementation of REST is not always more efficient than the replica exchange method (REM). Specifically, we find that exchanges between folded (F) and unfolded (U) conformations with vastly different structural energies are greatly reduced by the nonappearance of the water self-interaction energy in the replica exchange acceptance probabilities. REST, however, is expected to remain useful for a large class of systems for which the energy gap between the two states is not large, such as weakly bound protein–ligand complexes. Alternatively, a shell of water molecules can be incorporated into the central group, as discussed in the original paper. PMID:17439169

Accessing Secondary Markets as a Capital Source for Energy Efficiency Finance Programs: Program Design Considerations for Policymakers and Administrators

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kramer, C.; Martin, E. Fadrhonc; Thompson, P.

Estimates of the total opportunity for investment in cost-effective energy efficiency in the United States are typically in the range of several hundred billion dollars (Choi Granade, et al., 2009 and Fulton & Brandenburg, 2012).1,2 To access this potential, many state policymakers and utility regulators have established aggressive energy efficiency savings targets. Current levels of taxpayer and utility bill-payer funding for energy efficiency is only a small fraction of the total investment needed to meet these targets (SEE Action Financing Solutions Working Group, 2013). Given this challenge, some energy efficiency program administrators are working to access private capital sources withmore » the aim of amplifying the funds available for investment. In this context, efficient access to secondary market capital has been advanced as one important enabler of the energy efficiency industry “at scale.”3 The question of what role secondary markets can play in bringing energy efficiency to scale is largely untested despite extensive attention from media, technical publications, advocates, and others. Only a handful of transactions of energy efficiency loan products have been executed to date, and it is too soon to draw robust conclusions from these deals. At the same time, energy efficiency program administrators and policymakers face very real decisions regarding whether and how to access secondary markets as part of their energy efficiency deployment strategy.« less

Efficient micromagnetics for magnetic storage devices

NASA Astrophysics Data System (ADS)

Escobar Acevedo, Marco Antonio

Micromagnetics is an important component for advancing the magnetic nanostructures understanding and design. Numerous existing and prospective magnetic devices rely on micromagnetic analysis, these include hard disk drives, magnetic sensors, memories, microwave generators, and magnetic logic. The ability to examine, describe, and predict the magnetic behavior, and macroscopic properties of nanoscale magnetic systems is essential for improving the existing devices, for progressing in their understanding, and for enabling new technologies. This dissertation describes efficient micromagnetic methods as required for magnetic storage analysis. Their performance and accuracy is demonstrated by studying realistic, complex, and relevant micromagnetic system case studies. An efficient methodology for dynamic micromagnetics in large scale simulations is used to study the writing process in a full scale model of a magnetic write head. An efficient scheme, tailored for micromagnetics, to find the minimum energy state on a magnetic system is presented. This scheme can be used to calculate hysteresis loops. An efficient scheme, tailored for micromagnetics, to find the minimum energy path between two stable states on a magnetic system is presented. This minimum energy path is intimately related to the thermal stability.

SQDFT: Spectral Quadrature method for large-scale parallel O ( N ) Kohn–Sham calculations at high temperature

DOE Office of Scientific and Technical Information (OSTI.GOV)

Suryanarayana, Phanish; Pratapa, Phanisri P.; Sharma, Abhiraj

We present SQDFT: a large-scale parallel implementation of the Spectral Quadrature (SQ) method formore » $$\\mathscr{O}(N)$$ Kohn–Sham Density Functional Theory (DFT) calculations at high temperature. Specifically, we develop an efficient and scalable finite-difference implementation of the infinite-cell Clenshaw–Curtis SQ approach, in which results for the infinite crystal are obtained by expressing quantities of interest as bilinear forms or sums of bilinear forms, that are then approximated by spatially localized Clenshaw–Curtis quadrature rules. We demonstrate the accuracy of SQDFT by showing systematic convergence of energies and atomic forces with respect to SQ parameters to reference diagonalization results, and convergence with discretization to established planewave results, for both metallic and insulating systems. Here, we further demonstrate that SQDFT achieves excellent strong and weak parallel scaling on computer systems consisting of tens of thousands of processors, with near perfect $$\\mathscr{O}(N)$$ scaling with system size and wall times as low as a few seconds per self-consistent field iteration. Finally, we verify the accuracy of SQDFT in large-scale quantum molecular dynamics simulations of aluminum at high temperature.« less

Large-scale optimization-based non-negative computational framework for diffusion equations: Parallel implementation and performance studies

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chang, Justin; Karra, Satish; Nakshatrala, Kalyana B.

It is well-known that the standard Galerkin formulation, which is often the formulation of choice under the finite element method for solving self-adjoint diffusion equations, does not meet maximum principles and the non-negative constraint for anisotropic diffusion equations. Recently, optimization-based methodologies that satisfy maximum principles and the non-negative constraint for steady-state and transient diffusion-type equations have been proposed. To date, these methodologies have been tested only on small-scale academic problems. The purpose of this paper is to systematically study the performance of the non-negative methodology in the context of high performance computing (HPC). PETSc and TAO libraries are, respectively, usedmore » for the parallel environment and optimization solvers. For large-scale problems, it is important for computational scientists to understand the computational performance of current algorithms available in these scientific libraries. The numerical experiments are conducted on the state-of-the-art HPC systems, and a single-core performance model is used to better characterize the efficiency of the solvers. Furthermore, our studies indicate that the proposed non-negative computational framework for diffusion-type equations exhibits excellent strong scaling for real-world large-scale problems.« less

SQDFT: Spectral Quadrature method for large-scale parallel O ( N ) Kohn–Sham calculations at high temperature

DOE PAGES

Suryanarayana, Phanish; Pratapa, Phanisri P.; Sharma, Abhiraj; ...

2017-12-07

We present SQDFT: a large-scale parallel implementation of the Spectral Quadrature (SQ) method formore » $$\\mathscr{O}(N)$$ Kohn–Sham Density Functional Theory (DFT) calculations at high temperature. Specifically, we develop an efficient and scalable finite-difference implementation of the infinite-cell Clenshaw–Curtis SQ approach, in which results for the infinite crystal are obtained by expressing quantities of interest as bilinear forms or sums of bilinear forms, that are then approximated by spatially localized Clenshaw–Curtis quadrature rules. We demonstrate the accuracy of SQDFT by showing systematic convergence of energies and atomic forces with respect to SQ parameters to reference diagonalization results, and convergence with discretization to established planewave results, for both metallic and insulating systems. Here, we further demonstrate that SQDFT achieves excellent strong and weak parallel scaling on computer systems consisting of tens of thousands of processors, with near perfect $$\\mathscr{O}(N)$$ scaling with system size and wall times as low as a few seconds per self-consistent field iteration. Finally, we verify the accuracy of SQDFT in large-scale quantum molecular dynamics simulations of aluminum at high temperature.« less

Large-scale optimization-based non-negative computational framework for diffusion equations: Parallel implementation and performance studies

DOE PAGES

Chang, Justin; Karra, Satish; Nakshatrala, Kalyana B.

2016-07-26

It is well-known that the standard Galerkin formulation, which is often the formulation of choice under the finite element method for solving self-adjoint diffusion equations, does not meet maximum principles and the non-negative constraint for anisotropic diffusion equations. Recently, optimization-based methodologies that satisfy maximum principles and the non-negative constraint for steady-state and transient diffusion-type equations have been proposed. To date, these methodologies have been tested only on small-scale academic problems. The purpose of this paper is to systematically study the performance of the non-negative methodology in the context of high performance computing (HPC). PETSc and TAO libraries are, respectively, usedmore » for the parallel environment and optimization solvers. For large-scale problems, it is important for computational scientists to understand the computational performance of current algorithms available in these scientific libraries. The numerical experiments are conducted on the state-of-the-art HPC systems, and a single-core performance model is used to better characterize the efficiency of the solvers. Furthermore, our studies indicate that the proposed non-negative computational framework for diffusion-type equations exhibits excellent strong scaling for real-world large-scale problems.« less

Research on the Application of Rapid Surveying and Mapping for Large Scare Topographic Map by Uav Aerial Photography System

NASA Astrophysics Data System (ADS)

Gao, Z.; Song, Y.; Li, C.; Zeng, F.; Wang, F.

2017-08-01

Rapid acquisition and processing method of large scale topographic map data, which relies on the Unmanned Aerial Vehicle (UAV) low-altitude aerial photogrammetry system, is studied in this paper, elaborating the main work flow. Key technologies of UAV photograph mapping is also studied, developing a rapid mapping system based on electronic plate mapping system, thus changing the traditional mapping mode and greatly improving the efficiency of the mapping. Production test and achievement precision evaluation of Digital Orth photo Map (DOM), Digital Line Graphic (DLG) and other digital production were carried out combined with the city basic topographic map update project, which provides a new techniques for large scale rapid surveying and has obvious technical advantage and good application prospect.

Transfection microarray and the applications.

PubMed

Miyake, Masato; Yoshikawa, Tomohiro; Fujita, Satoshi; Miyake, Jun

2009-05-01

Microarray transfection has been extensively studied for high-throughput functional analysis of mammalian cells. However, control of efficiency and reproducibility are the critical issues for practical use. By using solid-phase transfection accelerators and nano-scaffold, we provide a highly efficient and reproducible microarray-transfection device, "transfection microarray". The device would be applied to the limited number of available primary cells and stem cells not only for large-scale functional analysis but also reporter-based time-lapse cellular event analysis.

Improved L-BFGS diagonal preconditioners for a large-scale 4D-Var inversion system: application to CO2 flux constraints and analysis error calculation

NASA Astrophysics Data System (ADS)

Bousserez, Nicolas; Henze, Daven; Bowman, Kevin; Liu, Junjie; Jones, Dylan; Keller, Martin; Deng, Feng

2013-04-01

This work presents improved analysis error estimates for 4D-Var systems. From operational NWP models to top-down constraints on trace gas emissions, many of today's data assimilation and inversion systems in atmospheric science rely on variational approaches. This success is due to both the mathematical clarity of these formulations and the availability of computationally efficient minimization algorithms. However, unlike Kalman Filter-based algorithms, these methods do not provide an estimate of the analysis or forecast error covariance matrices, these error statistics being propagated only implicitly by the system. From both a practical (cycling assimilation) and scientific perspective, assessing uncertainties in the solution of the variational problem is critical. For large-scale linear systems, deterministic or randomization approaches can be considered based on the equivalence between the inverse Hessian of the cost function and the covariance matrix of analysis error. For perfectly quadratic systems, like incremental 4D-Var, Lanczos/Conjugate-Gradient algorithms have proven to be most efficient in generating low-rank approximations of the Hessian matrix during the minimization. For weakly non-linear systems though, the Limited-memory Broyden-Fletcher-Goldfarb-Shanno (L-BFGS), a quasi-Newton descent algorithm, is usually considered the best method for the minimization. Suitable for large-scale optimization, this method allows one to generate an approximation to the inverse Hessian using the latest m vector/gradient pairs generated during the minimization, m depending upon the available core memory. At each iteration, an initial low-rank approximation to the inverse Hessian has to be provided, which is called preconditioning. The ability of the preconditioner to retain useful information from previous iterations largely determines the efficiency of the algorithm. Here we assess the performance of different preconditioners to estimate the inverse Hessian of a large-scale 4D-Var system. The impact of using the diagonal preconditioners proposed by Gilbert and Le Maréchal (1989) instead of the usual Oren-Spedicato scalar will be first presented. We will also introduce new hybrid methods that combine randomization estimates of the analysis error variance with L-BFGS diagonal updates to improve the inverse Hessian approximation. Results from these new algorithms will be evaluated against standard large ensemble Monte-Carlo simulations. The methods explored here are applied to the problem of inferring global atmospheric CO2 fluxes using remote sensing observations, and are intended to be integrated with the future NASA Carbon Monitoring System.

Fish Gill Inspired Crossflow for Efficient and Continuous Collection of Spilled Oil.

PubMed

Dou, Yuhai; Tian, Dongliang; Sun, Ziqi; Liu, Qiannan; Zhang, Na; Kim, Jung Ho; Jiang, Lei; Dou, Shi Xue

2017-03-28

Developing an effective system to clean up large-scale oil spills is of great significance due to their contribution to severe environmental pollution and destruction. Superwetting membranes have been widely studied for oil/water separation. The separation, however, adopts a gravity-driven approach that is inefficient and discontinuous due to quick fouling of the membrane by oil. Herein, inspired by the crossflow filtration behavior in fish gills, we propose a crossflow approach via a hydrophilic, tilted gradient membrane for spilled oil collection. In crossflow collection, as the oil/water flows parallel to the hydrophilic membrane surface, water is gradually filtered through the pores, while oil is repelled, transported, and finally collected for storage. Owing to the selective gating behavior of the water-sealed gradient membrane, the large pores at the bottom with high water flux favor fast water filtration, while the small pores at the top with strong oil repellency allow easy oil transportation. In addition, the gradient membrane exhibits excellent antifouling properties due to the protection of the water layer. Therefore, this bioinspired crossflow approach enables highly efficient and continuous spilled oil collection, which is very promising for the cleanup of large-scale oil spills.

Finite-difference method Stokes solver (FDMSS) for 3D pore geometries: Software development, validation and case studies

NASA Astrophysics Data System (ADS)

Gerke, Kirill M.; Vasilyev, Roman V.; Khirevich, Siarhei; Collins, Daniel; Karsanina, Marina V.; Sizonenko, Timofey O.; Korost, Dmitry V.; Lamontagne, Sébastien; Mallants, Dirk

2018-05-01

Permeability is one of the fundamental properties of porous media and is required for large-scale Darcian fluid flow and mass transport models. Whilst permeability can be measured directly at a range of scales, there are increasing opportunities to evaluate permeability from pore-scale fluid flow simulations. We introduce the free software Finite-Difference Method Stokes Solver (FDMSS) that solves Stokes equation using a finite-difference method (FDM) directly on voxelized 3D pore geometries (i.e. without meshing). Based on explicit convergence studies, validation on sphere packings with analytically known permeabilities, and comparison against lattice-Boltzmann and other published FDM studies, we conclude that FDMSS provides a computationally efficient and accurate basis for single-phase pore-scale flow simulations. By implementing an efficient parallelization and code optimization scheme, permeability inferences can now be made from 3D images of up to 109 voxels using modern desktop computers. Case studies demonstrate the broad applicability of the FDMSS software for both natural and artificial porous media.

Efficient implicit LES method for the simulation of turbulent cavitating flows

DOE Office of Scientific and Technical Information (OSTI.GOV)

Egerer, Christian P., E-mail: christian.egerer@aer.mw.tum.de; Schmidt, Steffen J.; Hickel, Stefan

2016-07-01

We present a numerical method for efficient large-eddy simulation of compressible liquid flows with cavitation based on an implicit subgrid-scale model. Phase change and subgrid-scale interface structures are modeled by a homogeneous mixture model that assumes local thermodynamic equilibrium. Unlike previous approaches, emphasis is placed on operating on a small stencil (at most four cells). The truncation error of the discretization is designed to function as a physically consistent subgrid-scale model for turbulence. We formulate a sensor functional that detects shock waves or pseudo-phase boundaries within the homogeneous mixture model for localizing numerical dissipation. In smooth regions of the flowmore » field, a formally non-dissipative central discretization scheme is used in combination with a regularization term to model the effect of unresolved subgrid scales. The new method is validated by computing standard single- and two-phase test-cases. Comparison of results for a turbulent cavitating mixing layer obtained with the new method demonstrates its suitability for the target applications.« less

Plant, microbial and ecosystem carbon use efficiencies interact to stabilize microbial growth as a fraction of gross primary production.

PubMed

Sinsabaugh, Robert L; Moorhead, Daryl L; Xu, Xiaofeng; Litvak, Marcy E

2017-06-01

The carbon use efficiency of plants (CUE a ) and microorganisms (CUE h ) determines rates of biomass turnover and soil carbon sequestration. We evaluated the hypothesis that CUE a and CUE h counterbalance at a large scale, stabilizing microbial growth (μ) as a fraction of gross primary production (GPP). Collating data from published studies, we correlated annual CUE a , estimated from satellite imagery, with locally determined soil CUE h for 100 globally distributed sites. Ecosystem CUE e , the ratio of net ecosystem production (NEP) to GPP, was estimated for each site using published models. At the ecosystem scale, CUE a and CUE h were inversely related. At the global scale, the apparent temperature sensitivity of CUE h with respect to mean annual temperature (MAT) was similar for organic and mineral soils (0.029°C -1 ). CUE a and CUE e were inversely related to MAT, with apparent sensitivities of -0.009 and -0.032°C -1 , respectively. These trends constrain the ratio μ : GPP (= (CUE a  × CUE h )/(1 - CUE e )) with respect to MAT by counterbalancing the apparent temperature sensitivities of the component processes. At the ecosystem scale, the counterbalance is effected by modulating soil organic matter stocks. The results suggest that a μ : GPP value of c. 0.13 is a homeostatic steady state for ecosystem carbon fluxes at a large scale. © 2017 The Authors. New Phytologist © 2017 New Phytologist Trust.

Cost of Community Integrated Prevention Campaign for Malaria, HIV, and Diarrhea in Rural Kenya

PubMed Central

2011-01-01

Background Delivery of community-based prevention services for HIV, malaria, and diarrhea is a major priority and challenge in rural Africa. Integrated delivery campaigns may offer a mechanism to achieve high coverage and efficiency. Methods We quantified the resources and costs to implement a large-scale integrated prevention campaign in Lurambi Division, Western Province, Kenya that reached 47,133 individuals (and 83% of eligible adults) in 7 days. The campaign provided HIV testing, condoms, and prevention education materials; a long-lasting insecticide-treated bed net; and a water filter. Data were obtained primarily from logistical and expenditure data maintained by implementing partners. We estimated the projected cost of a Scaled-Up Replication (SUR), assuming reliance on local managers, potential efficiencies of scale, and other adjustments. Results The cost per person served was $41.66 for the initial campaign and was projected at $31.98 for the SUR. The SUR cost included 67% for commodities (mainly water filters and bed nets) and 20% for personnel. The SUR projected unit cost per person served, by disease, was $6.27 for malaria (nets and training), $15.80 for diarrhea (filters and training), and $9.91 for HIV (test kits, counseling, condoms, and CD4 testing at each site). Conclusions A large-scale, rapidly implemented, integrated health campaign provided services to 80% of a rural Kenyan population with relatively low cost. Scaling up this design may provide similar services to larger populations at lower cost per person. PMID:22189090

Controlling Inventory: Real-World Mathematical Modeling

ERIC Educational Resources Information Center

Edwards, Thomas G.; Özgün-Koca, S. Asli; Chelst, Kenneth R.

2013-01-01

Amazon, Walmart, and other large-scale retailers owe their success partly to efficient inventory management. For such firms, holding too little inventory risks losing sales, whereas holding idle inventory wastes money. Therefore profits hinge on the inventory level chosen. In this activity, students investigate a simplified inventory-control…

Molecular Identification of XY Sex-Reversed Female and YY Male Channel Catfish

USDA-ARS?s Scientific Manuscript database

Production of channel catfish leads U.S. aquaculture, and monosex culture may provide higher production efficiencies. Determination of phenotypic sex is labor intensive and not practical for large scale culture. Catfish have an X-Y sex determination system with monomorphic sex chromosomes. Hormonal...

Equipment Efficiency for Healthy School Meals. [Videotape].

ERIC Educational Resources Information Center

National Food Service Management Inst., University, MS.

A satellite seminar on large-scale food production equipment discusses ways child nutrition personnel can maximize use of existing equipment, considers research related to use of existing equipment, explains plan reviews for equipment selection and purchase, and explores new equipment options. Examples illustrate use of planning or modernizing…

Systems and Cascades in Cognitive Development and Academic Achievement

ERIC Educational Resources Information Center

Bornstein, Marc H.; Hahn, Chun-Shin; Wolke, Dieter

2013-01-01

A large-scale ("N" = 552) controlled multivariate prospective 14-year longitudinal study of a developmental cascade embedded in a developmental system showed that information-processing efficiency in infancy (4 months), general mental development in toddlerhood (18 months), behavior difficulties in early childhood (36 months),…

Strategic Planning Tools for Large-Scale Technology-Based Assessments

ERIC Educational Resources Information Center

Koomen, Marten; Zoanetti, Nathan

2018-01-01

Education systems are increasingly being called upon to implement new technology-based assessment systems that generate efficiencies, better meet changing stakeholder expectations, or fulfil new assessment purposes. These assessment systems require coordinated organisational effort to implement and can be expensive in time, skill and other…

The latest developments and outlook for hydrogen liquefaction technology

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ohlig, K.; Decker, L.

2014-01-29

Liquefied hydrogen is presently mainly used for space applications and the semiconductor industry. While clean energy applications, for e.g. the automotive sector, currently contribute to this demand with a small share only, their demand may see a significant boost in the next years with the need for large scale liquefaction plants exceeding the current plant sizes by far. Hydrogen liquefaction for small scale plants with a maximum capacity of 3 tons per day (tpd) is accomplished with a Brayton refrigeration cycle using helium as refrigerant. This technology is characterized by low investment costs but lower process efficiency and hence highermore » operating costs. For larger plants, a hydrogen Claude cycle is used, characterized by higher investment but lower operating costs. However, liquefaction plants meeting the potentially high demand in the clean energy sector will need further optimization with regard to energy efficiency and hence operating costs. The present paper gives an overview of the currently applied technologies, including their thermodynamic and technical background. Areas of improvement are identified to derive process concepts for future large scale hydrogen liquefaction plants meeting the needs of clean energy applications with optimized energy efficiency and hence minimized operating costs. Compared to studies in this field, this paper focuses on application of new technology and innovative concepts which are either readily available or will require short qualification procedures. They will hence allow implementation in plants in the close future.« less

Inlet Turbulence and Length Scale Measurements in a Large Scale Transonic Turbine Cascade

NASA Technical Reports Server (NTRS)

Thurman, Douglas; Flegel, Ashlie; Giel, Paul

2014-01-01

Constant temperature hotwire anemometry data were acquired to determine the inlet turbulence conditions of a transonic turbine blade linear cascade. Flow conditions and angles were investigated that corresponded to the take-off and cruise conditions of the Variable Speed Power Turbine (VSPT) project and to an Energy Efficient Engine (EEE) scaled rotor blade tip section. Mean and turbulent flowfield measurements including intensity, length scale, turbulence decay, and power spectra were determined for high and low turbulence intensity flows at various Reynolds numbers and spanwise locations. The experimental data will be useful for establishing the inlet boundary conditions needed to validate turbulence models in CFD codes.

Parallel computing for probabilistic fatigue analysis

NASA Technical Reports Server (NTRS)

Sues, Robert H.; Lua, Yuan J.; Smith, Mark D.

1993-01-01

This paper presents the results of Phase I research to investigate the most effective parallel processing software strategies and hardware configurations for probabilistic structural analysis. We investigate the efficiency of both shared and distributed-memory architectures via a probabilistic fatigue life analysis problem. We also present a parallel programming approach, the virtual shared-memory paradigm, that is applicable across both types of hardware. Using this approach, problems can be solved on a variety of parallel configurations, including networks of single or multiprocessor workstations. We conclude that it is possible to effectively parallelize probabilistic fatigue analysis codes; however, special strategies will be needed to achieve large-scale parallelism to keep large number of processors busy and to treat problems with the large memory requirements encountered in practice. We also conclude that distributed-memory architecture is preferable to shared-memory for achieving large scale parallelism; however, in the future, the currently emerging hybrid-memory architectures will likely be optimal.

Bioremediation efficiency of the largest scale artificial Porphyra yezoensis cultivation in the open sea in China.

PubMed

Wu, Hailong; Huo, Yuanzi; Zhang, Jianheng; Liu, Yuanyuan; Zhao, Yating; He, Peimin

2015-06-15

The bioremediation efficiency of China's largest scale Porphyra yezoensis cultivation for removing dissolved nutrients and controlling harmful algae was studied in the radial sandbanks waters of Jiangsu Province in the year 2012-2013. Mean nutrient concentration values in the P. yezoensis cultivation area were significantly lower than those in the non-cultivation area, especially during the cultivation season (p<0.05). Tissue nitrogen and phosphorus contents of seaweeds were 5.99-0.80% (dry weight (DW)) and 0.16-0.19% (DW), respectively. Production of P. yezoensis was 58950.87tons DW. Based on these values, 3688.15tons of tissue nitrogen and 105.61tons of tissue phosphorus were removed by harvesting P. yezoensis. The richness index of the red tide species Skeleton emacostatum declined from 0.32 to 0.05 during the P. yezoensis cultivation season. These results indicate that large-scale cultivation of P. yezoensis can be used to efficiently alleviate eutrophication and control harmful algae blooms in open sea. Copyright © 2015 Elsevier Ltd. All rights reserved.

Adaptive-Grid Methods for Phase Field Models of Microstructure Development

NASA Technical Reports Server (NTRS)

Provatas, Nikolas; Goldenfeld, Nigel; Dantzig, Jonathan A.

1999-01-01

In this work the authors show how the phase field model can be solved in a computationally efficient manner that opens a new large-scale simulational window on solidification physics. Our method uses a finite element, adaptive-grid formulation, and exploits the fact that the phase and temperature fields vary significantly only near the interface. We illustrate how our method allows efficient simulation of phase-field models in very large systems, and verify the predictions of solvability theory at intermediate undercooling. We then present new results at low undercoolings that suggest that solvability theory may not give the correct tip speed in that regime. We model solidification using the phase-field model used by Karma and Rappel.

GraphReduce: Processing Large-Scale Graphs on Accelerator-Based Systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sengupta, Dipanjan; Song, Shuaiwen; Agarwal, Kapil

2015-11-15

Recent work on real-world graph analytics has sought to leverage the massive amount of parallelism offered by GPU devices, but challenges remain due to the inherent irregularity of graph algorithms and limitations in GPU-resident memory for storing large graphs. We present GraphReduce, a highly efficient and scalable GPU-based framework that operates on graphs that exceed the device’s internal memory capacity. GraphReduce adopts a combination of edge- and vertex-centric implementations of the Gather-Apply-Scatter programming model and operates on multiple asynchronous GPU streams to fully exploit the high degrees of parallelism in GPUs with efficient graph data movement between the host andmore » device.« less

Role of Edges in Complex Network Epidemiology

NASA Astrophysics Data System (ADS)

Zhang, Hao; Jiang, Zhi-Hong; Wang, Hui; Xie, Fei; Chen, Chao

2012-09-01

In complex network epidemiology, diseases spread along contacting edges between individuals and different edges may play different roles in epidemic outbreaks. Quantifying the efficiency of edges is an important step towards arresting epidemics. In this paper, we study the efficiency of edges in general susceptible-infected-recovered models, and introduce the transmission capability to measure the efficiency of edges. Results show that deleting edges with the highest transmission capability will greatly decrease epidemics on scale-free networks. Basing on the message passing approach, we get exact mathematical solution on configuration model networks with edge deletion in the large size limit.

Remote detection of single emitters via optical waveguides

NASA Astrophysics Data System (ADS)

Then, Patrick; Razinskas, Gary; Feichtner, Thorsten; Haas, Philippe; Wild, Andreas; Bellini, Nicola; Osellame, Roberto; Cerullo, Giulio; Hecht, Bert

2014-05-01

The integration of lab-on-a-chip technologies with single-molecule detection techniques may enable new applications in analytical chemistry, biotechnology, and medicine. We describe a method based on the reciprocity theorem of electromagnetic theory to determine and optimize the detection efficiency of photons emitted by single quantum emitters through truncated dielectric waveguides of arbitrary shape positioned in their proximity. We demonstrate experimentally that detection of single quantum emitters via such waveguides is possible, confirming the predicted behavior of the detection efficiency. Our findings blaze the trail towards efficient lensless single-emitter detection compatible with large-scale optofluidic integration.

The relative efficiency of modular and non-modular networks of different size

PubMed Central

Tosh, Colin R.; McNally, Luke

2015-01-01

Most biological networks are modular but previous work with small model networks has indicated that modularity does not necessarily lead to increased functional efficiency. Most biological networks are large, however, and here we examine the relative functional efficiency of modular and non-modular neural networks at a range of sizes. We conduct a detailed analysis of efficiency in networks of two size classes: ‘small’ and ‘large’, and a less detailed analysis across a range of network sizes. The former analysis reveals that while the modular network is less efficient than one of the two non-modular networks considered when networks are small, it is usually equally or more efficient than both non-modular networks when networks are large. The latter analysis shows that in networks of small to intermediate size, modular networks are much more efficient that non-modular networks of the same (low) connective density. If connective density must be kept low to reduce energy needs for example, this could promote modularity. We have shown how relative functionality/performance scales with network size, but the precise nature of evolutionary relationship between network size and prevalence of modularity will depend on the costs of connectivity. PMID:25631996

Data-driven Climate Modeling and Prediction

NASA Astrophysics Data System (ADS)

Kondrashov, D. A.; Chekroun, M.

2016-12-01

Global climate models aim to simulate a broad range of spatio-temporal scales of climate variability with state vector having many millions of degrees of freedom. On the other hand, while detailed weather prediction out to a few days requires high numerical resolution, it is fairly clear that a major fraction of large-scale climate variability can be predicted in a much lower-dimensional phase space. Low-dimensional models can simulate and predict this fraction of climate variability, provided they are able to account for linear and nonlinear interactions between the modes representing large scales of climate dynamics, as well as their interactions with a much larger number of modes representing fast and small scales. This presentation will highlight several new applications by Multilayered Stochastic Modeling (MSM) [Kondrashov, Chekroun and Ghil, 2015] framework that has abundantly proven its efficiency in the modeling and real-time forecasting of various climate phenomena. MSM is a data-driven inverse modeling technique that aims to obtain a low-order nonlinear system of prognostic equations driven by stochastic forcing, and estimates both the dynamical operator and the properties of the driving noise from multivariate time series of observations or a high-end model's simulation. MSM leads to a system of stochastic differential equations (SDEs) involving hidden (auxiliary) variables of fast-small scales ranked by layers, which interact with the macroscopic (observed) variables of large-slow scales to model the dynamics of the latter, and thus convey memory effects. New MSM climate applications focus on development of computationally efficient low-order models by using data-adaptive decomposition methods that convey memory effects by time-embedding techniques, such as Multichannel Singular Spectrum Analysis (M-SSA) [Ghil et al. 2002] and recently developed Data-Adaptive Harmonic (DAH) decomposition method [Chekroun and Kondrashov, 2016]. In particular, new results by DAH-MSM modeling and prediction of Arctic Sea Ice, as well as decadal predictions of near-surface Earth temperatures will be presented.

Particle-In-Cell Simulations of a Thermionic Converter

NASA Astrophysics Data System (ADS)

Clark, S. E.

2017-12-01

Simulations of thermionic converters are presented where cesium is used as a work function reducing agent in a nano-fabricated triode configuration. The cathode and anode are spaced on the order of 100 μm, and the grid structure has features on the micron scale near the anode. The hot side is operated near 1600 K, the cold side near 600 K, and the converter has the potential to convert heat to DC electrical current upwards of 20% efficiency. Affordable and robust thermionic converters have the potential to displace century old mechanical engines and turbines as a primary means of electrical power generation in the near future. High efficiency converters that operate at a small scale could be used to generate power locally and alleviate the need for large scale power transmission systems. Electron and negative cesium ion back emission from the anode are considered, as well as device longevity and fabrication feasibility.

Scalable ion-photon quantum interface based on integrated diffractive mirrors

NASA Astrophysics Data System (ADS)

Ghadimi, Moji; Blūms, Valdis; Norton, Benjamin G.; Fisher, Paul M.; Connell, Steven C.; Amini, Jason M.; Volin, Curtis; Hayden, Harley; Pai, Chien-Shing; Kielpinski, David; Lobino, Mirko; Streed, Erik W.

2017-12-01

Quantum networking links quantum processors through remote entanglement for distributed quantum information processing and secure long-range communication. Trapped ions are a leading quantum information processing platform, having demonstrated universal small-scale processors and roadmaps for large-scale implementation. Overall rates of ion-photon entanglement generation, essential for remote trapped ion entanglement, are limited by coupling efficiency into single mode fibers and scaling to many ions. Here, we show a microfabricated trap with integrated diffractive mirrors that couples 4.1(6)% of the fluorescence from a 174Yb+ ion into a single mode fiber, nearly triple the demonstrated bulk optics efficiency. The integrated optic collects 5.8(8)% of the π transition fluorescence, images the ion with sub-wavelength resolution, and couples 71(5)% of the collected light into the fiber. Our technology is suitable for entangling multiple ions in parallel and overcomes mode quality limitations of existing integrated optical interconnects.

Particle-In-Cell Simulations of a Thermionic Converter

NASA Astrophysics Data System (ADS)

Clark, Stephen

2017-10-01

Simulations of thermionic converters are presented where cesium is used as a work function reducing agent in a nano-fabricated triode configuration. The cathode and anode are spaced on the order of 100 μm, and the grid structure has features on the micron scale near the anode. The hot side is operated near 1600 K, the cold side near 600 K, and the converter has the potential to convert heat to DC electrical current upwards of 20% efficiency. Affordable and robust thermionic converters have the potential to displace century old mechanical engines and turbines as a primary means of electrical power generation in the near future. High efficiency converters that operate at a small scale could be used to generate power locally and alleviate the need for large scale power transmission systems. Electron and negative cesium ion back emission from the anode are considered, as well as device longevity and fabrication feasibility.

Magnetorotational dynamo action in the shearing box

NASA Astrophysics Data System (ADS)

Walker, Justin; Boldyrev, Stanislav

2017-09-01

Magnetic dynamo action caused by the magnetorotational instability is studied in the shearing-box approximation with no imposed net magnetic flux. Consistent with recent studies, the dynamo action is found to be sensitive to the aspect ratio of the box: it is much easier to obtain in tall boxes (stretched in the direction normal to the disc plane) than in long boxes (stretched in the radial direction). Our direct numerical simulations indicate that the dynamo is possible in both cases, given a large enough magnetic Reynolds number. To explain the relatively larger effort required to obtain the dynamo action in a long box, we propose that the turbulent eddies caused by the instability most efficiently fold and mix the magnetic field lines in the radial direction. As a result, in the long box the scale of the generated strong azimuthal (stream-wise directed) magnetic field is always comparable to the scale of the turbulent eddies. In contrast, in the tall box the azimuthal magnetic flux spreads in the vertical direction over a distance exceeding the scale of the turbulent eddies. As a result, different vertical sections of the tall box are permeated by large-scale non-zero azimuthal magnetic fluxes, facilitating the instability. In agreement with this picture, the cases when the dynamo is efficient are characterized by a strong intermittency of the local azimuthal magnetic fluxes.

Graph Based Models for Unsupervised High Dimensional Data Clustering and Network Analysis

DTIC Science & Technology

2015-01-01

ApprovedOMB No. 0704-0188 Public reporting burden for the collection of information is estimated to average 1 hour per response, including the time for...algorithms we proposed improve the time e ciency signi cantly for large scale datasets. In the last chapter, we also propose an incremental reseeding...plume detection in hyper-spectral video data. These graph based clustering algorithms we proposed improve the time efficiency significantly for large

Cloud/climate sensitivity experiments

NASA Technical Reports Server (NTRS)

Roads, J. O.; Vallis, G. K.; Remer, L.

1982-01-01

A study of the relationships between large-scale cloud fields and large scale circulation patterns is presented. The basic tool is a multi-level numerical model comprising conservation equations for temperature, water vapor and cloud water and appropriate parameterizations for evaporation, condensation, precipitation and radiative feedbacks. Incorporating an equation for cloud water in a large-scale model is somewhat novel and allows the formation and advection of clouds to be treated explicitly. The model is run on a two-dimensional, vertical-horizontal grid with constant winds. It is shown that cloud cover increases with decreased eddy vertical velocity, decreased horizontal advection, decreased atmospheric temperature, increased surface temperature, and decreased precipitation efficiency. The cloud field is found to be well correlated with the relative humidity field except at the highest levels. When radiative feedbacks are incorporated and the temperature increased by increasing CO2 content, cloud amounts decrease at upper-levels or equivalently cloud top height falls. This reduces the temperature response, especially at upper levels, compared with an experiment in which cloud cover is fixed.

Do large-scale assessments measure students' ability to integrate scientific knowledge?

NASA Astrophysics Data System (ADS)

Lee, Hee-Sun

2010-03-01

Large-scale assessments are used as means to diagnose the current status of student achievement in science and compare students across schools, states, and countries. For efficiency, multiple-choice items and dichotomously-scored open-ended items are pervasively used in large-scale assessments such as Trends in International Math and Science Study (TIMSS). This study investigated how well these items measure secondary school students' ability to integrate scientific knowledge. This study collected responses of 8400 students to 116 multiple-choice and 84 open-ended items and applied an Item Response Theory analysis based on the Rasch Partial Credit Model. Results indicate that most multiple-choice items and dichotomously-scored open-ended items can be used to determine whether students have normative ideas about science topics, but cannot measure whether students integrate multiple pieces of relevant science ideas. Only when the scoring rubric is redesigned to capture subtle nuances of student open-ended responses, open-ended items become a valid and reliable tool to assess students' knowledge integration ability.

Exploring Cloud Computing for Large-scale Scientific Applications

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lin, Guang; Han, Binh; Yin, Jian

This paper explores cloud computing for large-scale data-intensive scientific applications. Cloud computing is attractive because it provides hardware and software resources on-demand, which relieves the burden of acquiring and maintaining a huge amount of resources that may be used only once by a scientific application. However, unlike typical commercial applications that often just requires a moderate amount of ordinary resources, large-scale scientific applications often need to process enormous amount of data in the terabyte or even petabyte range and require special high performance hardware with low latency connections to complete computation in a reasonable amount of time. To address thesemore » challenges, we build an infrastructure that can dynamically select high performance computing hardware across institutions and dynamically adapt the computation to the selected resources to achieve high performance. We have also demonstrated the effectiveness of our infrastructure by building a system biology application and an uncertainty quantification application for carbon sequestration, which can efficiently utilize data and computation resources across several institutions.« less

Utilisation of ISA Reverse Genetics and Large-Scale Random Codon Re-Encoding to Produce Attenuated Strains of Tick-Borne Encephalitis Virus within Days.

PubMed

de Fabritus, Lauriane; Nougairède, Antoine; Aubry, Fabien; Gould, Ernest A; de Lamballerie, Xavier

2016-01-01

Large-scale codon re-encoding is a new method of attenuating RNA viruses. However, the use of infectious clones to generate attenuated viruses has inherent technical problems. We previously developed a bacterium-free reverse genetics protocol, designated ISA, and now combined it with large-scale random codon-re-encoding method to produce attenuated tick-borne encephalitis virus (TBEV), a pathogenic flavivirus which causes febrile illness and encephalitis in humans. We produced wild-type (WT) and two re-encoded TBEVs, containing 273 or 273+284 synonymous mutations in the NS5 and NS5+NS3 coding regions respectively. Both re-encoded viruses were attenuated when compared with WT virus using a laboratory mouse model and the relative level of attenuation increased with the degree of re-encoding. Moreover, all infected animals produced neutralizing antibodies. This novel, rapid and efficient approach to engineering attenuated viruses could potentially expedite the development of safe and effective new-generation live attenuated vaccines.

Parallel Index and Query for Large Scale Data Analysis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chou, Jerry; Wu, Kesheng; Ruebel, Oliver

2011-07-18

Modern scientific datasets present numerous data management and analysis challenges. State-of-the-art index and query technologies are critical for facilitating interactive exploration of large datasets, but numerous challenges remain in terms of designing a system for process- ing general scientific datasets. The system needs to be able to run on distributed multi-core platforms, efficiently utilize underlying I/O infrastructure, and scale to massive datasets. We present FastQuery, a novel software framework that address these challenges. FastQuery utilizes a state-of-the-art index and query technology (FastBit) and is designed to process mas- sive datasets on modern supercomputing platforms. We apply FastQuery to processing ofmore » a massive 50TB dataset generated by a large scale accelerator modeling code. We demonstrate the scalability of the tool to 11,520 cores. Motivated by the scientific need to search for inter- esting particles in this dataset, we use our framework to reduce search time from hours to tens of seconds.« less

Network placement optimization for large-scale distributed system

NASA Astrophysics Data System (ADS)

Ren, Yu; Liu, Fangfang; Fu, Yunxia; Zhou, Zheng

2018-01-01

The network geometry strongly influences the performance of the distributed system, i.e., the coverage capability, measurement accuracy and overall cost. Therefore the network placement optimization represents an urgent issue in the distributed measurement, even in large-scale metrology. This paper presents an effective computer-assisted network placement optimization procedure for the large-scale distributed system and illustrates it with the example of the multi-tracker system. To get an optimal placement, the coverage capability and the coordinate uncertainty of the network are quantified. Then a placement optimization objective function is developed in terms of coverage capabilities, measurement accuracy and overall cost. And a novel grid-based encoding approach for Genetic algorithm is proposed. So the network placement is optimized by a global rough search and a local detailed search. Its obvious advantage is that there is no need for a specific initial placement. At last, a specific application illustrates this placement optimization procedure can simulate the measurement results of a specific network and design the optimal placement efficiently.

Multimode resource-constrained multiple project scheduling problem under fuzzy random environment and its application to a large scale hydropower construction project.

PubMed

Xu, Jiuping; Feng, Cuiying

2014-01-01

This paper presents an extension of the multimode resource-constrained project scheduling problem for a large scale construction project where multiple parallel projects and a fuzzy random environment are considered. By taking into account the most typical goals in project management, a cost/weighted makespan/quality trade-off optimization model is constructed. To deal with the uncertainties, a hybrid crisp approach is used to transform the fuzzy random parameters into fuzzy variables that are subsequently defuzzified using an expected value operator with an optimistic-pessimistic index. Then a combinatorial-priority-based hybrid particle swarm optimization algorithm is developed to solve the proposed model, where the combinatorial particle swarm optimization and priority-based particle swarm optimization are designed to assign modes to activities and to schedule activities, respectively. Finally, the results and analysis of a practical example at a large scale hydropower construction project are presented to demonstrate the practicality and efficiency of the proposed model and optimization method.

Multimode Resource-Constrained Multiple Project Scheduling Problem under Fuzzy Random Environment and Its Application to a Large Scale Hydropower Construction Project

PubMed Central

Xu, Jiuping

2014-01-01

This paper presents an extension of the multimode resource-constrained project scheduling problem for a large scale construction project where multiple parallel projects and a fuzzy random environment are considered. By taking into account the most typical goals in project management, a cost/weighted makespan/quality trade-off optimization model is constructed. To deal with the uncertainties, a hybrid crisp approach is used to transform the fuzzy random parameters into fuzzy variables that are subsequently defuzzified using an expected value operator with an optimistic-pessimistic index. Then a combinatorial-priority-based hybrid particle swarm optimization algorithm is developed to solve the proposed model, where the combinatorial particle swarm optimization and priority-based particle swarm optimization are designed to assign modes to activities and to schedule activities, respectively. Finally, the results and analysis of a practical example at a large scale hydropower construction project are presented to demonstrate the practicality and efficiency of the proposed model and optimization method. PMID:24550708

Efficiency of bulk-heterojunction organic solar cells

PubMed Central

Scharber, M.C.; Sariciftci, N.S.

2013-01-01

During the last years the performance of bulk heterojunction solar cells has been improved significantly. For a large-scale application of this technology further improvements are required. This article reviews the basic working principles and the state of the art device design of bulk heterojunction solar cells. The importance of high power conversion efficiencies for the commercial exploitation is outlined and different efficiency models for bulk heterojunction solar cells are discussed. Assuming state of the art materials and device architectures several models predict power conversion efficiencies in the range of 10–15%. A more general approach assuming device operation close to the Shockley–Queisser-limit leads to even higher efficiencies. Bulk heterojunction devices exhibiting only radiative recombination of charge carriers could be as efficient as ideal inorganic photovoltaic devices. PMID:24302787

A survey on routing protocols for large-scale wireless sensor networks.

PubMed

Li, Changle; Zhang, Hanxiao; Hao, Binbin; Li, Jiandong

2011-01-01

With the advances in micro-electronics, wireless sensor devices have been made much smaller and more integrated, and large-scale wireless sensor networks (WSNs) based the cooperation among the significant amount of nodes have become a hot topic. "Large-scale" means mainly large area or high density of a network. Accordingly the routing protocols must scale well to the network scope extension and node density increases. A sensor node is normally energy-limited and cannot be recharged, and thus its energy consumption has a quite significant effect on the scalability of the protocol. To the best of our knowledge, currently the mainstream methods to solve the energy problem in large-scale WSNs are the hierarchical routing protocols. In a hierarchical routing protocol, all the nodes are divided into several groups with different assignment levels. The nodes within the high level are responsible for data aggregation and management work, and the low level nodes for sensing their surroundings and collecting information. The hierarchical routing protocols are proved to be more energy-efficient than flat ones in which all the nodes play the same role, especially in terms of the data aggregation and the flooding of the control packets. With focus on the hierarchical structure, in this paper we provide an insight into routing protocols designed specifically for large-scale WSNs. According to the different objectives, the protocols are generally classified based on different criteria such as control overhead reduction, energy consumption mitigation and energy balance. In order to gain a comprehensive understanding of each protocol, we highlight their innovative ideas, describe the underlying principles in detail and analyze their advantages and disadvantages. Moreover a comparison of each routing protocol is conducted to demonstrate the differences between the protocols in terms of message complexity, memory requirements, localization, data aggregation, clustering manner and other metrics. Finally some open issues in routing protocol design in large-scale wireless sensor networks and conclusions are proposed.

cOSPREY: A Cloud-Based Distributed Algorithm for Large-Scale Computational Protein Design

PubMed Central

Pan, Yuchao; Dong, Yuxi; Zhou, Jingtian; Hallen, Mark; Donald, Bruce R.; Xu, Wei

2016-01-01

Abstract Finding the global minimum energy conformation (GMEC) of a huge combinatorial search space is the key challenge in computational protein design (CPD) problems. Traditional algorithms lack a scalable and efficient distributed design scheme, preventing researchers from taking full advantage of current cloud infrastructures. We design cloud OSPREY (cOSPREY), an extension to a widely used protein design software OSPREY, to allow the original design framework to scale to the commercial cloud infrastructures. We propose several novel designs to integrate both algorithm and system optimizations, such as GMEC-specific pruning, state search partitioning, asynchronous algorithm state sharing, and fault tolerance. We evaluate cOSPREY on three different cloud platforms using different technologies and show that it can solve a number of large-scale protein design problems that have not been possible with previous approaches. PMID:27154509

The Explorer of Diffuse Galactic Emission (EDGE): Determining the Large-Scale Structure Evolution in the Universe

NASA Technical Reports Server (NTRS)

Silverberg, R. F.; Cheng, E. S.; Cottingham, D. A.; Fixsen, D. J.; Meyer, S. S.; Knox, L.; Timbie, P.; Wilson, G.

2003-01-01

Measurements of the large-scale anisotropy of the Cosmic Infared Background (CIB) can be used to determine the characteristics of the distribution of galaxies at the largest spatial scales. With this information important tests of galaxy evolution models and primordial structure growth are possible. In this paper, we describe the scientific goals, instrumentation, and operation of EDGE, a mission using an Antarctic Long Duration Balloon (LDB) platform. EDGE will osbserve the anisotropy in the CIB in 8 spectral bands from 270 GHz-1.5 THz with 6 arcminute angular resolution over a region -400 square degrees. EDGE uses a one-meter class off-axis telescope and an array of Frequency Selective Bololeters (FSB) to provide the compact and efficient multi-colar, high sensitivity radiometer required to achieve its scientific objectives.

Are the traditional large-scale drought indices suitable for shallow water wetlands? An example in the Everglades.

PubMed

Zhao, Dehua; Wang, Penghe; Zuo, Jie; Zhang, Hui; An, Shuqing; Ramesh, Reddy K

2017-08-01

Numerous drought indices have been developed over the past several decades. However, few studies have focused on the suitability of indices for studies of ephemeral wetlands. The objective is to answer the following question: can the traditional large-scale drought indices characterize drought severity in shallow water wetlands such as the Everglades? The question was approached from two perspectives: the available water quantity and the response of wetland ecosystems to drought. The results showed the unsuitability of traditional large-scale drought indices for characterizing the actual available water quantity based on two findings. (1) Large spatial variations in precipitation (P), potential evapotranspiration (PE), water table depth (WTD) and the monthly water storage change (SC) were observed in the Everglades; notably, the spatial variation in SC, which reflects the monthly water balance, was 1.86 and 1.62 times larger than the temporal variation between seasons and between years, respectively. (2) The large-scale water balance measured based on the water storage variation had an average indicating efficiency (IE) of only 60.01% due to the redistribution of interior water. The spatial distribution of variations in the Normalized Different Vegetation Index (NDVI) in the 2011 dry season showed significantly positive, significantly negative and weak correlations with the minimum WTD in wet prairies, graminoid prairies and sawgrass wetlands, respectively. The significant and opposite correlations imply the unsuitability of the traditional large-scale drought indices in evaluating the effect of drought on shallow water wetlands. Copyright © 2017 Elsevier Ltd. All rights reserved.

Streamline curvature in supersonic shear layers

NASA Technical Reports Server (NTRS)

Kibens, V.

1992-01-01

Results of an experimental investigation in which a curved shear layer was generated between supersonic flow from a rectangular converging/diverging nozzle and the freestream in a series of open channels with varying radii of curvature are reported. The shear layers exhibit unsteady large-scale activity at supersonic pressure ratios, indicating increased mixing efficiency. This effect contrasts with supersonic flow in a straight channel, for which no large-scale vortical structure development occurs. Curvature must exceed a minimum level before it begins to affect the dynamics of the supersonic shear layer appreciably. The curved channel flows are compared with reference flows consisting of a free jet, a straight channel, and wall jets without sidewalls on a flat and a curved plate.

Requirements and principles for the implementation and construction of large-scale geographic information systems

NASA Technical Reports Server (NTRS)

Smith, Terence R.; Menon, Sudhakar; Star, Jeffrey L.; Estes, John E.

1987-01-01

This paper provides a brief survey of the history, structure and functions of 'traditional' geographic information systems (GIS), and then suggests a set of requirements that large-scale GIS should satisfy, together with a set of principles for their satisfaction. These principles, which include the systematic application of techniques from several subfields of computer science to the design and implementation of GIS and the integration of techniques from computer vision and image processing into standard GIS technology, are discussed in some detail. In particular, the paper provides a detailed discussion of questions relating to appropriate data models, data structures and computational procedures for the efficient storage, retrieval and analysis of spatially-indexed data.

Effect of dislocations on the open-circuit voltage, short-circuit current and efficiency of heteroepitaxial indium phosphide solar cells

NASA Technical Reports Server (NTRS)

Jain, Raj K.; Flood, Dennis J.

1990-01-01

Excellent radiation resistance of indium phosphide solar cells makes them a promising candidate for space power applications, but the present high cost of starting substrates may inhibit their large scale use. Thin film indium phosphide cells grown on Si or GaAs substrates have exhibited low efficiencies, because of the generation and propagation of large number of dislocations. Dislocation densities were calculated and its influence on the open circuit voltage, short circuit current, and efficiency of heteroepitaxial indium phosphide cells was studied using the PC-1D. Dislocations act as predominant recombination centers and are required to be controlled by proper transition layers and improved growth techniques. It is shown that heteroepitaxial grown cells could achieve efficiencies in excess of 18 percent AMO by controlling the number of dislocations. The effect of emitter thickness and surface recombination velocity on the cell performance parameters vs. dislocation density is also studied.

Numerical flow simulation and efficiency prediction for axial turbines by advanced turbulence models

NASA Astrophysics Data System (ADS)

Jošt, D.; Škerlavaj, A.; Lipej, A.

2012-11-01

Numerical prediction of an efficiency of a 6-blade Kaplan turbine is presented. At first, the results of steady state analysis performed by different turbulence models for different operating regimes are compared to the measurements. For small and optimal angles of runner blades the efficiency was quite accurately predicted, but for maximal blade angle the discrepancy between calculated and measured values was quite large. By transient analysis, especially when the Scale Adaptive Simulation Shear Stress Transport (SAS SST) model with zonal Large Eddy Simulation (ZLES) in the draft tube was used, the efficiency was significantly improved. The improvement was at all operating points, but it was the largest for maximal discharge. The reason was better flow simulation in the draft tube. Details about turbulent structure in the draft tube obtained by SST, SAS SST and SAS SST with ZLES are illustrated in order to explain the reasons for differences in flow energy losses obtained by different turbulence models.

PROBLEM OF FORMING IN A MAN-OPERATOR A HABIT OF TRACKING A MOVING TARGET,

DTIC Science & Technology

Cybernetics stimulated the large-scale use of the method of functional analogy which makes it possible to compare technical and human activity systems...interesting and highly efficient human activity because of the psychological control factor involved in its operation. The human tracking system is

3 CFR 13502 - Executive Order 13502 of February 6, 2009. Use of Project Labor Agreements for Federal...

Code of Federal Regulations, 2010 CFR

2010-01-01

... developing by providing structure and stability to large-scale construction projects, thereby promoting the... procurement, producing labor-management stability, and ensuring compliance with laws and regulations governing... construction projects receiving Federal financial assistance, would help to promote the economical, efficient...

Energy Storage for the Power Grid

ScienceCinema

Imhoff, Carl; Vaishnav, Dave; Wang, Wei

2018-05-30

The iron vanadium redox flow battery was developed by researchers at Pacific Northwest National Laboratory as a solution to large-scale energy storage for the power grid. This technology provides the energy industry and the nation with a reliable, stable, safe, and low-cost storage alternative for a cleaner, efficient energy future.

Acquiring data for large aquatic resource surveys: the art of ompromise among science, logistics, and reality

EPA Science Inventory

The US Environmental Protection Agency (EPA) is revising its strategy to obtain the information needed to answer questions pertinent to water-quality management efficiently and rigorously at national scales. One tool of this revised strategy is use of statistically based surveys ...

Architectural and Mobility Management Designs in Internet-Based Infrastructure Wireless Mesh Networks

ERIC Educational Resources Information Center

Zhao, Weiyi

2011-01-01

Wireless mesh networks (WMNs) have recently emerged to be a cost-effective solution to support large-scale wireless Internet access. They have numerous applications, such as broadband Internet access, building automation, and intelligent transportation systems. One research challenge for Internet-based WMNs is to design efficient mobility…

Carbon and water vapor fluxes of different ecosystems in Oklahoma

USDA-ARS?s Scientific Manuscript database

Information on exchange of energy, carbon dioxide (CO2), and water vapor (H2O) for major terrestrial ecosystems is vital to quantify carbon and water balances on a large-scale. It is also necessary to develop, test, and improve crop models and satellite-based production efficiency and evapotranspira...

A Short History of Performance Assessment: Lessons Learned.

ERIC Educational Resources Information Center

Madaus, George F.; O'Dwyer, Laura M.

1999-01-01

Places performance assessment in the context of high-stakes uses, describes underlying technologies, and outlines the history of performance testing from 210 B.C.E. to the present. Historical issues of fairness, efficiency, cost, and infrastructure influence contemporary efforts to use performance assessments in large-scale, high-stakes testing…

Large Scale IR Evaluation

ERIC Educational Resources Information Center

Pavlu, Virgil

2008-01-01

Today, search engines are embedded into all aspects of digital world: in addition to Internet search, all operating systems have integrated search engines that respond even as you type, even over the network, even on cell phones; therefore the importance of their efficacy and efficiency cannot be overstated. There are many open possibilities for…

Controlled reflectance surfaces with film-coupled colloidal nanoantennas

PubMed Central

Moreau, Antoine; Ciraci, Cristian; Mock, Jack J.; Hill, Ryan T.; Wang, Qiang; Wiley, Benjamin J.; Chilkoti, Ashutosh; Smith, David R.

2013-01-01

Efficient and tunable absorption is essential for a variety of applications, such as the design of controlled emissivity surfaces for thermophotovoltaic devices1; tailoring of the infrared spectrum for controlled thermal dissipation2; and detector elements for imaging3. Metamaterials based on metallic elements are particularly efficient as absorbing media, because both the electrical and the magnetic properties of a metamaterial can be tuned by structured design4. To date, metamaterial absorbers in the infrared or visible range have been fabricated using lithographically patterned metallic structures2,5–9, making them inherently difficult to produce over large areas and hence reducing their applicability. We demonstrate here an extraordinarily simple method to create a metamaterial absorber by randomly adsorbing chemically synthesized silver nanocubes onto a nanoscale thick polymer spacer layer on a gold film –making no effort to control the spatial arrangement of the cubes on the film– and show that the film-coupled nanocubes provide a reflectance spectrum that can be tailored by varying the geometry. Each nanocube is the optical analog of the well-known grounded patch antenna, with a nearly identical local field structure that is modified by the plasmonic response of the metal dielectric function, and with an anomalously large absorption efficiency that can be partly attributed to an interferometric effect10. The absorptivity of large surface areas can be controlled using this method, at scales out of reach of lithographic approaches like e-beam lithography otherwise required to manipulate matter at the nanometer scale. PMID:23222613

Detecting communities in large networks

NASA Astrophysics Data System (ADS)

Capocci, A.; Servedio, V. D. P.; Caldarelli, G.; Colaiori, F.

2005-07-01

We develop an algorithm to detect community structure in complex networks. The algorithm is based on spectral methods and takes into account weights and link orientation. Since the method detects efficiently clustered nodes in large networks even when these are not sharply partitioned, it turns to be specially suitable for the analysis of social and information networks. We test the algorithm on a large-scale data-set from a psychological experiment of word association. In this case, it proves to be successful both in clustering words, and in uncovering mental association patterns.

Inversion of very large matrices encountered in large scale problems of photogrammetry and photographic astrometry

NASA Technical Reports Server (NTRS)

Brown, D. C.

1971-01-01

The simultaneous adjustment of very large nets of overlapping plates covering the celestial sphere becomes computationally feasible by virtue of a twofold process that generates a system of normal equations having a bordered-banded coefficient matrix, and solves such a system in a highly efficient manner. Numerical results suggest that when a well constructed spherical net is subjected to a rigorous, simultaneous adjustment, the exercise of independently established control points is neither required for determinancy nor for production of accurate results.

Efficiency and economics of large scale hydrogen liquefaction. [for future generation aircraft requirements

NASA Technical Reports Server (NTRS)

Baker, C. R.

1975-01-01

Liquid hydrogen is being considered as a substitute for conventional hydrocarbon-based fuels for future generations of commercial jet aircraft. Its acceptance will depend, in part, upon the technology and cost of liquefaction. The process and economic requirements for providing a sufficient quantity of liquid hydrogen to service a major airport are described. The design is supported by thermodynamic studies which determine the effect of process arrangement and operating parameters on the process efficiency and work of liquefaction.

Comparison of Multi-Scale Digital Elevation Models for Defining Waterways and Catchments Over Large Areas

NASA Astrophysics Data System (ADS)

Harris, B.; McDougall, K.; Barry, M.

2012-07-01

Digital Elevation Models (DEMs) allow for the efficient and consistent creation of waterways and catchment boundaries over large areas. Studies of waterway delineation from DEMs are usually undertaken over small or single catchment areas due to the nature of the problems being investigated. Improvements in Geographic Information Systems (GIS) techniques, software, hardware and data allow for analysis of larger data sets and also facilitate a consistent tool for the creation and analysis of waterways over extensive areas. However, rarely are they developed over large regional areas because of the lack of available raw data sets and the amount of work required to create the underlying DEMs. This paper examines definition of waterways and catchments over an area of approximately 25,000 km2 to establish the optimal DEM scale required for waterway delineation over large regional projects. The comparative study analysed multi-scale DEMs over two test areas (Wivenhoe catchment, 543 km2 and a detailed 13 km2 within the Wivenhoe catchment) including various data types, scales, quality, and variable catchment input parameters. Historic and available DEM data was compared to high resolution Lidar based DEMs to assess variations in the formation of stream networks. The results identified that, particularly in areas of high elevation change, DEMs at 20 m cell size created from broad scale 1:25,000 data (combined with more detailed data or manual delineation in flat areas) are adequate for the creation of waterways and catchments at a regional scale.

Improved efficiency of a large-area Cu(In,Ga)Se₂ solar cell by a nontoxic hydrogen-assisted solid Se vapor selenization process.

PubMed

Wu, Tsung-Ta; Hu, Fan; Huang, Jyun-Hong; Chang, Chia-ho; Lai, Chih-chung; Yen, Yu-Ting; Huang, Hou-Ying; Hong, Hwen-Fen; Wang, Zhiming M; Shen, Chang-Hong; Shieh, Jia-Min; Chueh, Yu-Lun

2014-04-09

A nontoxic hydrogen-assisted solid Se vapor selenization process (HASVS) technique to achieve a large-area (40 × 30 cm(2)) Cu(In,Ga)Se2 (CIGS) solar panel with enhanced efficiencies from 7.1 to 10.8% (12.0% for active area) was demonstrated. The remarkable improvement of efficiency and fill factor comes from improved open circuit voltage (Voc) and reduced dark current due to (1) decreased interface recombination raised from the formation of a widened buried homojunction with n-type Cd(Cu) participation and (2) enhanced separation of electron and hole carriers resulting from the accumulation of Na atoms on the surface of the CIGS film. The effects of microstructural, compositional, and electrical characteristics with hydrogen-assisted Se vapor selenization, including interdiffusion of atoms and formation of buried homojunction, were examined in detail. This methodology can be also applied to CIS (CuInSe2) thin film solar cells with enhanced efficiencies from 5.3% to 8.5% (9.4% for active area) and provides a facile approach to improve quality of CIGS and stimulate the nontoxic progress in the large scale CIGS PV industry.

Efficient purification and concentration of viruses from a large body of high turbidity seawater.

PubMed

Sun, Guowei; Xiao, Jinzhou; Wang, Hongming; Gong, Chaowen; Pan, Yingjie; Yan, Shuling; Wang, Yongjie

2014-01-01

Marine viruses are the most abundant entities in the ocean and play crucial roles in the marine ecological system. However, understanding of viral diversity on large scale depends on efficient and reliable viral purification and concentration techniques. Here, we report on developing an efficient method to purify and concentrate viruses from large body of high turbidity seawater. The developed method characterizes with high viral recovery efficiency, high concentration factor, high viral particle densities and high-throughput, and is reliable for viral concentration from high turbidity seawater. Recovered viral particles were used directly for subsequent analysis by epifluorescence microscopy, transmission electron microscopy and metagenomic sequencing. Three points are essential for this method:•The sampled seawater (>150 L) was initially divided into two parts, water fraction and settled matter fraction, after natural sedimentation.•Both viruses in the water fraction concentrated by tangential flow filtration (TFF) and viruses isolated from the settled matter fraction were considered as the whole viral community in high turbidity seawater.•The viral concentrates were re-concentrated by using centrifugal filter device in order to obtain high density of viral particles.

Numerical methods for large eddy simulation of acoustic combustion instabilities

NASA Astrophysics Data System (ADS)

Wall, Clifton T.

Acoustic combustion instabilities occur when interaction between the combustion process and acoustic modes in a combustor results in periodic oscillations in pressure, velocity, and heat release. If sufficiently large in amplitude, these instabilities can cause operational difficulties or the failure of combustor hardware. In many situations, the dominant instability is the result of the interaction between a low frequency acoustic mode of the combustor and the large scale hydrodynamics. Large eddy simulation (LES), therefore, is a promising tool for the prediction of these instabilities, since both the low frequency acoustic modes and the large scale hydrodynamics are well resolved in LES. Problems with the tractability of such simulations arise, however, due to the difficulty of solving the compressible Navier-Stokes equations efficiently at low Mach number and due to the large number of acoustic periods that are often required for such instabilities to reach limit cycles. An implicit numerical method for the solution of the compressible Navier-Stokes equations has been developed which avoids the acoustic CFL restriction, allowing for significant efficiency gains at low Mach number, while still resolving the low frequency acoustic modes of interest. In the limit of a uniform grid the numerical method causes no artificial damping of acoustic waves. New, non-reflecting boundary conditions have also been developed for use with the characteristic-based approach of Poinsot and Lele (1992). The new boundary conditions are implemented in a manner which allows for significant reduction of the computational domain of an LES by eliminating the need to perform LES in regions where one-dimensional acoustics significantly affect the instability but details of the hydrodynamics do not. These new numerical techniques have been demonstrated in an LES of an experimental combustor. The new techniques are shown to be an efficient means of performing LES of acoustic combustion instabilities and are shown to accurately predict the occurrence and frequency of the dominant mode of the instability observed in the experiment.

Establishment of an efficient virus-induced gene silencing (VIGS) assay in Arabidopsis by Agrobacterium-mediated rubbing infection.

PubMed

Manhães, Ana Marcia E de A; de Oliveira, Marcos V V; Shan, Libo

2015-01-01

Several VIGS protocols have been established for high-throughput functional genomic screens as it bypasses the time-consuming and laborious process of generation of transgenic plants. The silencing efficiency in this approach is largely hindered by a technically demanding step in which the first pair of newly emerged true leaves at the 2-week-old stage are infiltrated with a needleless syringe. To further optimize VIGS efficiency and achieve rapid inoculation for a large-scale functional genomic study, here we describe a protocol of an efficient VIGS assay in Arabidopsis using Agrobacterium-mediated rubbing infection. The Agrobacterium inoculation is performed by simply rubbing the leaves with Filter Agent Celite(®) 545. The highly efficient and uniform silencing effect was indicated by the development of a visibly albino phenotype due to silencing of the Cloroplastos alterados 1 (CLA1) gene in the newly emerged leaves. In addition, the albino phenotype could be observed in stems and flowers, indicating its potential application for gene functional studies in the late vegetative development and flowering stages.

Scalable Preconditioners for Structure Preserving Discretizations of Maxwell Equations in First Order Form

DOE PAGES

Phillips, Edward Geoffrey; Shadid, John N.; Cyr, Eric C.

2018-05-01

Here, we report multiple physical time-scales can arise in electromagnetic simulations when dissipative effects are introduced through boundary conditions, when currents follow external time-scales, and when material parameters vary spatially. In such scenarios, the time-scales of interest may be much slower than the fastest time-scales supported by the Maxwell equations, therefore making implicit time integration an efficient approach. The use of implicit temporal discretizations results in linear systems in which fast time-scales, which severely constrain the stability of an explicit method, can manifest as so-called stiff modes. This study proposes a new block preconditioner for structure preserving (also termed physicsmore » compatible) discretizations of the Maxwell equations in first order form. The intent of the preconditioner is to enable the efficient solution of multiple-time-scale Maxwell type systems. An additional benefit of the developed preconditioner is that it requires only a traditional multigrid method for its subsolves and compares well against alternative approaches that rely on specialized edge-based multigrid routines that may not be readily available. Lastly, results demonstrate parallel scalability at large electromagnetic wave CFL numbers on a variety of test problems.« less