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At least 145 records · Page 8

The power of event-driven analytics in Large Scale Data Processing

FeedZai is a software company specialized in creating high-­‐throughput low-­‐latency data processing solutions. FeedZai develops a product called "FeedZai Pulse" for continuous event-­‐driven analytics that makes application development easier for end users. It automatically calculates key performance indicators and baselines, showing how current performance differ from previous history, creating timely business intelligence updated to the second. The tool does predictive analytics and trend analysis, displaying data on real-­‐time web-­‐based graphics. In 2010 FeedZai won the European EBN Smart Entrepreneurship Competition, in the Digital Models category, being considered one of the "top-­‐20 smart companies in Europe". The main objective of this seminar/workshop is to explore the topic for large-­‐scale data processing using Complex Event Processing and, in particular, the possible uses of Pulse in the scope of the data processing needs of CERN. Pulse is available as open-­‐source and can be licensed both for non-­‐commercial and commercial applications. FeedZai is interested in exploring possible synergies with CERN in high-­‐volume low-­‐latency data processing applications. The seminar will be structured in two sessions, the first one being aimed to expose the general scope of FeedZai's activities, and the second focused on Pulse itself: 10:00-11:00 FeedZai and Large Scale Data Processing; Introduction to FeedZai; FeedZai Pulse and Complex Event Processing; Demonstration; Use-Cases and Applications; Conclusion and Q&A. 11:00-11:15 Coffee break 11:15-12:30 FeedZai Pulse Under the Hood; A First FeedZai Pulse Application; PulseQL overview; Defining KPIs and Baselines; Conclusion and Q&A. About the speakers Nuno Sebastião is the CEO of FeedZai. Having worked for many years for the European Space Agency (ESA), he was responsible the overall design and development of Satellite Simulation Infrastructure of the agency. Having left ESA to found FeedZai, Nuno is currently responsible for the whole operations of the company. Nuno holds an M.Eng. in Informatics Engineering for the University of Coimbra, and an MBA from the London Business School. Paulo Marques is the CTO of FeedZai, being responsible for product development. Paulo is an Assistant Professor at the University of Coimbra, in the area of Distributed Data Processing, and an Adjunct Associated Professor at Carnegie Mellon, in the US. In the past Paulo lead a large number of projects for institutions like the ESA, Microsoft Research, SciSys, Siemens, among others, being now fully dedicated to FeedZai. Paulo holds a Ph.D. in Distributed Systems from the University of Coimbra.

97 MATHEMATICS AND COMPUTING↗

ECP Software Technology Capability Assessment Report V3.0

The Exascale Computing Project (ECP) Software Technology (ST) focus area is responsible for (1) developing critical software capabilities that will enable the successful execution of ECP applications and (2) providing key components of a productive and sustainable exascale computing ecosystem that will position the US Department of Energy (DOE) and the broader high-performance computing (HPC) community with a firm foundation for future extreme-scale computing capabilities. This ECP ST Capability Assessment Report (CAR) provides an overview and assessment of current ECP ST capabilities and activities, giving stakeholders and the broader HPC community information that can be used to assess ECP ST progress and plan their own efforts accordingly. ECP ST leaders commit to updating this document on regular basis (every 6–12 months). Highlights from this version of the report are presented here. This version of the CAR contains the following updates relative to the previous revision: (1) This report highlights the progress with the Extreme-scale Scientific Software Stack (E4S) efforts. In particular, this report discusses how E4S continues to gain traction as a first-class entity in the HPC ecosystem, enabling new conversations with users, facilities, vendors, other US agencies, and international partners. (2) The several-page summaries of each ECP Level 4 project were updated to reflect recent progress and next steps (Section 4). Of particular note are the experiences of our teams on early-access systems for Frontier. (3) The E4S is described further. E4S is now updated via quarterly releases. E4S is the primary integration and delivery vehicle for ECP ST capabilities (Section 2.1.1). (4) The ECP ST software development kit (SDK) effort further refined its groupings (Section 2.1.2). The ECP ST focus area represents the key bridge between exascale systems and the scientists developing applications that will run on those platforms. ECP ST efforts contribute to approximately 70 software products (Section 2.1.3) in six technical areas (Table 1). Since publishing the previous revision of the CAR, the team has continued to evolve the product dictionary of official product names, which enables more rigorous mapping of ECP ST deliverables to stakeholders (Section 2.1.4).

97 MATHEMATICS AND COMPUTING↗

Post Irradiation Capabilities at the Idaho National Laboratory

The U.S. Department of Energy (DOE), Office of Nuclear Energy (NE) oversees the efforts to ensure nuclear energy remains a viable option for the United States. A significant portion of these efforts are related to post-irradiation examinations (PIE) of highly activated fuel and materials that are subject to the extreme environment inside a nuclear reactor. As the lead national laboratory, Idaho National Laboratory (INL) has a rich history, experience, workforce and capabilities for performing PIE. However, new advances in tools and techniques for performing PIE now enable understanding the performance of fuels and materials at the nano-scale and smaller level. Examination at this level is critical since this is the scale at which irradiation damage occurs. The INL is on course to adopt these advanced tools and techniques to develop a comprehensive nuclear fuels and materials characterization capability that is unique in the world. Because INL has extensive PIE capabilities currently in place, a strong foundation exist to build upon as new capabilities are implemented and work load increases. In the recent past, INL has adopted significant capability to perform advanced PIE characterization. Looking forward, INL is planning for the addition of two facilities that will be built to meet the stringent demands of advanced tools and techniques for highly activated fuels and materials characterization. Dubbed the Irradiated Materials Characterization Laboratory (IMCL) and Advanced Post Irradiation Examination Capability , these facilities are next generation PIE laboratories designed to perform the work of PIE that cannot be performed in current DOE facilities. In addition to physical capabilities, INL has recently added two significant contributors to the Advanced Test Reactor-National Scientific User Facility (ATR-NSUF), Oak Ridge National Laboratory and University of California, Berkeley.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Durability challenges and perspective in the development of PGM-free electrocatalysts for the oxygen reduction reaction

Significant advancement in the development of highly active platinum group metal-free (PGM-free) electrocatalysts is giving rise to the possibility of a low-cost replacement for Pt electrocatalysts in polymer electrolyte fuel cells. However, before the successful implementation of PGM-free electrocatalysts, the challenge of long-term stability under fuel cell operating conditions needs to be addressed. In this paper, the current status of PGM-free electrocatalyst performance and durability is reviewed. A perspective on the route for the study of degradation mechanisms in PGM-free electrocatalysts in both half-cell and membrane electrode assembly environments is presented. The analysis of proposed degradation mechanisms suggests classification into two relevant length scales: atomic scale and macro/mesoscale. Finally, an overview of different characterization techniques (both experimental and theoretical) for studying different possible degradation mechanisms is outlined. Directly addressing the underlying mechanisms leading to loss of activity in PGM-free electrocatalysts will provide valuable insight necessary for the development of next-generation materials with improved durability capable of competing with Pt-based counterparts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

U.S. Commercial Spent Nuclear Fuel Assembly Characteristics - 1968-2013

Activities related to management of spent nuclear fuel (SNF) are increasing in the US and many other countries. Over 240,000 SNF assemblies have been discharged from US commercial reactors since the late 1960s. The enrichment and burnup of SNF have changed significantly over the past 40 years, and fuel assembly designs have also evolved. Understanding the general characteristics of SNF helps regulators and other stakeholders form overall strategies towards the final disposal of US SNF. This report documents a survey of all US commercial SNF assemblies in the GC-859 database and provides reference SNF source terms (e.g., nuclide inventories, decay heat, and neutron/photon emission) at various cooling times up to 200 years after fuel discharge. This study reviews the distribution and evolution of fuel parameters of all SNF assemblies discharged over the past 40 years. Assemblies were categorized into three groups based on discharge year, and the median burnups and enrichments of each group were used to establish representative cases. An extended burnup case was created for boiling water reactor (BWR) fuels, and another was created for the pressurized water reactor (PWR) fuels. Two additional cases were developed to represent the eight mixed oxide (MOX) fuel assemblies in the database. Burnup calculations were performed for each representative case. Realistic parameters for fuel design and operations were used to model the SNF and to provide reference fuel characteristics representative of the current inventory. Burnup calculations were performed using the ORIGEN code, which is part of the SCALE nuclear modeling and simulation code system. Results include total activity, decay heat, photon emission, neutron flux, gamma heat, and plutonium content, as well as concentrations for 115 significant nuclides. These quantities are important in the design, regulation, and operations of SNF storage, transportation, and disposal systems.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Best practices for experiments and reporting in photocatalytic CO 2 reduction

Visible-light-driven conversion of CO 2 to fuels and valuable compounds has experienced tremendous activity in recent years, aiming at storing solar energy into chemical bonds using CO 2 as a renewable feedstock, ultimately at massive scale. Despite these efforts, processes and catalytic systems are still at an early stage of development, with fundamental mechanistic challenges as pre-requisites for device design. In this context, collective efforts currently necessitate the exploration of a variety of approaches. On the other hand, an alignment of practices is required to ensure robustness, precision and accuracy of the results, as well as shared metrics and tools for advancing our understanding of the necessary processes. Here, this Perspective aims to provide guidelines and a framework towards these objectives.

photocatalysis↗

Marine Corps Base Camp Lejeune Geospatial Marsh Model: Elevation Maps

Critical military training and testing on lands along the nation’s coastal and estuarine shorelines are increasingly placed at risk because of encroachment pressures in surrounding areas, impairments due to other anthropogenic disturbances, and changes in climate and sea level. The U.S. Department of Defense (DoD) intends to enhance and sustain its training and testing assets and also optimize its stewardship of natural resources through the development and application of an ecosystem-based management approach on DoD installations. To accomplish this goal, particularly for installations in estuarine/coastal environments, the Strategic Environmental Research and Development Program (SERDP) launched the Defense Coastal/Estuarine Research Program (DCERP) as a 10-year effort at Marine Corps Base Camp Lejeune (MCBCL) in North Carolina. The results of the second 5 years of the program (DCERP2) are presented in the DCERP2 Final Report.There were four overarching objectives of DCERP2. The first objective was to understand the effects of climate change impacts, including warming temperatures, variability in the hydrological cycle, storm events, and sea level rise on the coastal ecosystems at MCBCL from observations and measurements made over the 10-year program. The second objective was to understand the carbon cycle of the coastal and terrestrial ecosystems at MCBCL through a highly integrated sampling program. The third objective was to develop models, tools, and indicators to evaluate current and projected future ecosystem state changes and translate scientific findings into actionable information for installation managers. The last objective was to recommend adaptive management strategies to sustain ecosystem natural resources within the context of an active military installation.This data package contains PNGs of elevation maps (w/ scale bars) for Freeman, Trapps, and French marsh modeling domains in the target years 2013 (initial), 2035, 2065, & 2100 after modeling marsh under the five sea level rise (SLR) scenarios provided by the base.

54 ENVIRONMENTAL SCIENCES↗

Package Development for Reliability Testing of Perovskites

Metal halide perovskite solar cells have reached a critical point in their development. At a current certified record efficiency of 25.7% for a single-junction, research-scale cell, they now garner serious attention from the solar cell industry as a promising route to widespread, low-cost photovoltaics in single- or tandem-junction configurations. However, more work to demonstrate their durability under real-world outdoor test conditions is necessary to ensure the long-term success and deployment of the technology. Differences in chemistry, processes, and their combination result in unique performance limiters for both efficiency and stability. Further, as many active formulations and layer/cell stack combinations are sensitive to temperature, air, and moisture, it is important to separate intrinsic limitations to stability relative to these extrinsic sources. This presents a particular need for the development of an appropriate and reliable package for environmental (i.e., accelerated and outdoor) testing that will permit these different factors to be evaluated and understood.

14 SOLAR ENERGY↗

Combined convective and diffusive simulations: VERB-4D comparison with 17 March 2013 Van Allen Probes observations: VERB-4D

Our study focused on understanding the coupling between different electron populations in the inner magnetosphere and the various physical processes that determine evolution of electron fluxes at different energies. Observations during the 17 March 2013 storm and simulations with a newly developed Versatile Electron Radiation Belt-4D (VERB-4D) are presented. This analysis of the drift trajectories of the energetic and relativistic electrons shows that electron trajectories at transitional energies with a first invariant on the scale of ~100 MeV/G may resemble ring current or relativistic electron trajectories depending on the level of geomagnetic activity. Simulations with the VERB-4D code including convection, radial diffusion, and energy diffusion are presented. Sensitivity simulations including various physical processes show how different acceleration mechanisms contribute to the energization of energetic electrons at transitional energies. In particular, the range of energies where inward transport is strongly influenced by both convection and radial diffusion are studied. Our results of the 4-D simulations are compared to Van Allen Probes observations at a range of energies including source, seed, and core populations of the energetic and relativistic electrons in the inner magnetosphere.

58 GEOSCIENCES↗

Development of Rhodococcus opacus as a chassis for lignin valorization and bioproduction of high-value compounds

The current extraction and use of fossil fuels has been linked to extensive negative health and environmental outcomes. Lignocellulosic biomass-derived biofuels and bioproducts are being actively considered as renewable alternatives to the fuels, chemicals, and materials produced from fossil fuels. A major challenge limiting large-scale, economic deployment of second-generation biorefineries is the insufficient product yield, diversity, and value that current conversion technologies can extract from lignocellulose, in particular from the underutilized lignin fraction. Rhodococcus opacus PD630 is an oleaginous gram-positive bacterium with innate catabolic pathways and tolerance mechanisms for the inhibitory aromatic compounds found in depolymerized lignin, as well as native or engineered pathways for hexose and pentose sugars found in the carbohydrate fractions of biomass. As a result, R. opacus holds potential as a biological chassis for the conversion of lignocellulosic biomass into biodiesel precursors and other value-added products. This review begins by examining the important role that lignin utilization will play in the future of biorefineries and by providing a concise survey of the current lignin conversion technologies. The genetic machinery and capabilities of R. opacus that allow the bacterium to tolerate and metabolize aromatic compounds and depolymerized lignin are also discussed, along with a synopsis of the genetic toolbox and synthetic biology methods now available for engineering this organism. Finally, we summarize the different feedstocks that R. opacus has been demonstrated to consume, and the high-value products that it has been shown to produce. Engineered R. opacus will enable lignin valorization over the coming years, leading to cost-effective conversion of lignocellulose into fuels, chemicals, and materials.

09 BIOMASS FUELS↗

pnnl/socialsim

The goal of Computational Simulation of Online Social Behavior (SocialSim) is to develop innovative technologies for highfidelity computational simulation of online social behavior. SocialSim will focus specifically on information spread and evolution. Current computational approaches to social and behavioral simulation are limited in this regard. Top-down simulation approaches focus on the dynamics of a population as a whole, and model behavioral phenomena by assuming uniform or mostly-uniform behavior across that population. Such methods can easily scale to simulate massive populations, but can be inaccurate if there are specific, distinct variations in the characteristics of the population. In contrast, bottom-up simulation approaches treat population dynamics as an emergent property of the activities and interactions taking place within a diverse population. While such approaches can enable more accurate simulation of information spread, they do not readily scale to represent large populations. SocialSim aims to develop novel approaches to address these challenges.

Smith, William↗

A general mechanistic framework for cross-scale understanding of hot spots and hot moments in carbon and water fluxes

Semi-arid ecosystems, like those in the American Southwest, exert a massive impact on the interannual variability of carbon and water cycling. Unfortunately, these carbon and water fluxes are notoriously difficult to predict due to their high spatial and temporal variability, which is poorly captured by the current generation of vegetation models. Indeed, this region is exemplified by the ‘hot spots and hot moments’ concept, which states that small areas in space (‘hot spots’) and transient moments in time (‘hot moments’) exert an outsized influence on biogeochemical cycling. However, the factors that regulate these pulses in biogeochemical activity are unknown, as is their variability across space and time. These uncertainties severely limit efforts to better represent hot spots and hot moments in models. Here, we seek to develop a generalized method for detecting and quantifying the importance of hot spots and hot moments from individual plant to regional scales. Underpinning this method is our recently developed statistical approach for identifying hot spots and hot moments. By applying this method to semi-continuous measurements of plant water status, a depth profile of soil water potential, and ecosystem fluxes via eddy covariance, we will track the fate of water through the soil-plant-atmosphere continuum and identify the mechanistic drivers of these transient pulses in biogeochemical activity. Then, we will expand this approach across a broad network of Ameriflux towers, and apply a machine learning approach that will allow us to upscale measurements of hot spots and hot moments across the American Southwest and quantify their impact on carbon and water cycles. These products will allow us to identify hot spots and hot moments across spatio-temporal scales and will serve as crucial data sources for validating a new generation of models that can better capture highly dynamic carbon and water fluxes. The proposed method will be easily transferable across biomes and will serve as a framework for future research on hot spots and hot moments across the plant ecophysiology, biometeorology, and vegetation modeling communities.

54 ENVIRONMENTAL SCIENCES↗

Use of Convolutional Neural Network Image Classification and High-Speed Ion Probe Data Toward Real-Time Detonation Characterization in a Water-Cooled Rotating Detonation Engine

As rotating detonation engines (RDEs) progress in maturity, the importance of monitoring advancements toward development of active control becomes more critical. Experimental RDE data processing at time scales which satisfy real-time diagnostics will likely require the use of machine learning. This study aims to develop and deploy a novel real-time monitoring technique capable of determining detonation wave number, direction, frequency, and individual wave speeds throughout experimental RDE operational windows. To do so, the diagnostic integrates image classification by a convolutional neural network (CNN) and ionization current signal analysis. Wave mode identification through single-image CNN classification bypasses the need to evaluate sequential images and offers instantaneous identification of the wave mode present in the RDE annulus. Here, real-time processing speeds are achieved due to low data volumes required by the methodology, namely one short-exposure image and a short window of sensor data to generate each diagnostic output. The diagnostic acquires live data using a modified experimental setup alongside Pylon and PyDAQmx libraries within a python data acquisition environment. Lab-deployed diagnostic results are presented across varying wave modes, operating conditions, and data quality, currently executed at 3–4 Hz with a variety of iteration speed optimization options to be considered as future work. These speeds exceed that of conventional techniques and offer a proven structure for real-time RDE monitoring. The demonstrated ability to analyze detonation wave presence and behavior during RDE operation will certainly play a vital role in the development of RDE active control, necessary for RDE technology maturation toward industrial integration.

42 ENGINEERING↗

Environmental Monitoring and Risk Assessment for Marine Energy Systems

There is a growing interest in marine energy development around the world, but the industry is still in its early stages, with only a limited number of small-scale deployments thus far. One significant challenge lies in understanding and mitigating the potential environmental impact of deploying and operating marine energy systems on aquatic animals. To address these challenges, many monitoring technologies and risk assessment tools have been developed or are currently in development. This chapter delves into these technologies, such as biotelemetry, passive acoustic monitoring, active sonars, and autonomous sensors, to underscore their significant and practical applications.

Deng, Zhiqun↗

Pushing HTCondor and glideinWMS to 200K+ Jobs in a Global Pool for CMS before Run 2

The CMS experiment at the LHC relies on HTCondor and glideinWMS as its primary batch and pilot-based Grid provisioning system. So far we have been running several independent resource pools, but we are working on unifying them all to reduce the operational load and more effectively share resources between various activities in CMS. The major challenge of this unification activity is scale. The combined pool size is expected to reach 200K job slots, which is significantly bigger than any other multi-user HTCondor based system currently in production. To get there we have studied scaling limitations in our existing pools, the biggest of which tops out at about 70K slots, providing valuable feedback to the development communities, who have responded by delivering improvements which have helped us reach higher and higher scales with more stability. We have also worked on improving the organization and support model for this critical service during Run 2 of the LHC. This contribution will present the results of the scale testing and experiences from the first months of running the Global Pool.

Balcas, J.↗

Improving Coal-Fired Plant Performance Through Integrated Predictive and Condition-Based Monitoring Tools

The project demonstrated the ability to improve boiler performance and reliability through the integrated use of condition-based monitoring (CBM) and predictions of the impacts of coal quality on boiler operations at a full-scale coal-fired power plant. The advanced tool developed actively monitors and manages coal quality and overall boiler conditions that maximizes availability and maintains generating capacity while reducing cost. The tool is used to forecast and alert plant operators and engineers about poor boiler conditions which may occur as a result of incoming coal and/or current power plant operating conditions. The Combustion System Performance Indices (CSPI) and CoalTracker (CT) programs predicts fireside performance of the plant including slagging, fouling, erosion, slag flow, strength development (sintering/densification), and slag layer thickness based on the composition of delivered coal. CT program is tailored for each plant and is used to track the coal from the point of delivery to the burner. The most successful application of the CSPI-CT has been at plants where the coal composition is determined through the use of a full stream elemental analyzers based on prompt gamma neutron analysis (PGNAA). The CSPI-CT program information is used by coal procurement, coal mining and plant operations personnel to select and blend coal properties for the best plant performance.

01 COAL, LIGNITE, AND PEAT↗

Generation of Turbulence in Colliding Reconnection Jets

The collision of magnetic reconnection jets is reported on by means of a three-dimensional numerical simulation at the kinetic scale, in the presence of a strong guide field. We demonstrate that turbulence develops due to the collision of jets, producing several current sheets in reconnection outflows, aligned with the guide field direction. The turbulence is mainly two-dimensional, with stronger gradients in the plane perpendicular to the guide field and low wave-like activity in the parallel direction. First, we provide a numerical method to isolate the central turbulent region. Second, we analyze the spatial second-order structure function and prove that turbulence is confined in this region. Lastly, we compute local magnetic and electric frequency spectra, finding a trend in the subion range that differs from typical cases for which the Taylor hypothesis is valid, as well as wave activity in the range between ion and electron cyclotron frequencies. Our findings are relevant to understand observed collisions of reconnection jets in space plasmas.

79 ASTRONOMY AND ASTROPHYSICS↗