PROCESS FLOW DIAGRAMS AND NODE DESCRIPTIONS FOR THE SNF WMS
Explore the source record for details and available documents.
SEARCH · Search NASA
Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
Explore the source record for details and available documents.
The plenary panel focused on government and industry world leaders speaking on the pressing issues facing radioactive waste management in 2020 and beyond. Panelists included an OECD/ NEA representative for the international community, a Huntington Ingalls Industries representative for the commercial sector, and the US DOE Senior Advisor to the Under Secretary of Science representing DOE Environmental Management. Panelists with presentations: WM2020 Speech (Michael Lempke); Optimization: A Better Path toward Managing Nuclear Decommissioning and Legacies (William Magwood); Update On the DOE Environmental Management Program (William White)
Wyandotte Municipal Services (WMS), a Michigan Municipal Utility offering electric generation, transmission & distribution, water filtration & distribution and Broadband/Video sought to deploy a set of renewable energy projects for their Electric Utility that contributed to reducing the City’s environmental and energy impact, provided examples that would encourage businesses and citizens to adopt cleaner energy practices and help WMS meet the required renewable energy standards of the State of Michigan (10% in 2015, 15% in 2021). WMS generates and delivers roughly 280,000 megawatt hours (MWh) of electricity annually to more than 10,000 homes and 1,000 businesses within the City of Wyandotte. The Wyandotte Integrated Renewable Energy Strategy – WIRES 2 resulted in deployment of a set of community-scale micro-wind turbines, evaluation and installation of energy-efficient and low-maintenance light-emitting diode (LED) street lights and park lights in highly visible locations in the City and expansion of the geothermal heating and cooling district that already included residential geothermal systems, to include larger scale business/institutional systems at the Utility’s largest electric customer and at the City Library. Finally, WMS identified the need for job training in energy efficiency and renewable energy technologies to further develop a local skilled workforce in these areas. Partially funded by the grant, the wind turbine project provides a benchmark for WMS, local businesses and residents in the evaluation of utility-scale wind v. micro-wind in an urban environment as a renewable energy strategy. Also partially funded by the grant, the LED project benefited the City of Wyandotte by reducing load on the electric system for the public utility but also reduced City costs for streetlighting, parking lot lighting and park lighting without a compromise in security. The project also resulted in a visual success that has led to additional approvals for non-Grant related LED lighting installations resulting in further reduction in the electric load in the City. Commercial Geothermal installations resulted in the Utility being able to eliminate steam customers who formerly utilized the byproduct of steam from WMS electric production. Due to the reduction in natural gas prices and the overall reduction in market purchased power, it was no longer feasible for WMS to operate its Power Plant as a base load plant and to only operate on a market dispatch philosophy when market prices dictated that WMS could produce electricity cheaper than the market purchase price. This has resulted in fewer operating days for the WMS Power Plant, resulting in less environmental impact. WMS has now completely exited the steam business and the ability to offer a geothermal option to two (2) former steam customers (BASF-Wyandotte and the Bacon Memorial Library) allowed for that. In addition, peak loads have been shaved for these two (2) large customers due to the consistent temperature offered by geothermal heating and cooling, reducing the swings associated with thermostat changes caused by outside temperature changes during extreme high and low temperatures. Finally, energy efficiency and renewable energy college-level classes at Wayne County Community College allowed a group of interested students to pursue studies in those technologies through grant provided tuition, books and course materials. This effort provided a foundation of potential future employees not only for WMS but other energy efficiency/renewable energy employers such as Franklin Energy, a partner with WMS in energy optimization efforts with Wyandotte businesses.
A method of calibration-free scanned-wavelength modulation spectroscopy (WMS) absorption sensing is provided by obtaining absorption lineshape measurements of a gas sample on a sensor using 1f-normalized WMS-2f where an injection current to an injection current-tunable diode laser (TDL) is modulated at a frequency f, where a wavelength modulation and an intensity modulation of the TDL are simultaneously generated, extracting using a numerical lock-in program and a low-pass filter appropriate band-width WMS-nf (n=1, 2, . . . ) signals, where the WMS-nf signals are harmonics of the f, determining a physical property of the gas sample according to ratios of the WMS-nf signals, determining the zero-absorption background using scanned-wavelength WMS, and determining non-absorption losses using at least two of the harmonics, where a need for a non-absorption baseline measurement is removed from measurements in environments where collision broadening has blended transition linewidths, where calibration free WMS measurements without knowledge of the transition linewidth is enabled.
A ppb-level mid-infrared ethane (C 2 H 6 ) sensor was developed using a continuous-wave, thermoelectrically cooled, distributed feedback interband cascade laser emitting at 3.34 μm and a miniature dense patterned multipass gas cell with a 54.6-m optical path length. The performance of the sensor was investigated using two different techniques based on the tunable interband cascade laser: direct absorption spectroscopy (DAS) and second-harmonic wavelength modulation spectroscopy (2f-WMS). Three measurement schemes, DAS, WMS and quasi-simultaneous DAS and WMS, were realized based on the same optical sensor core. A detection limit of ~7.92 ppbv with a precision of ±30 ppbv for the separate DAS scheme with an averaging time of 1 s and a detection limit of ~1.19 ppbv with a precision of about ±4 ppbv for the separate WMS scheme with a 4-s averaging time were achieved. An Allan–Werle variance analysis indicated that the precisions can be further improved to 777 pptv @ 166 s for the separate DAS scheme and 269 pptv @ 108 s for the WMS scheme, respectively. For the quasi-simultaneous DAS and WMS scheme, both the 2f signal and the direct absorption signal were simultaneously extracted using a LabVIEW platform, and four C 2 H 6 samples (0, 30, 60 and 90 ppbv with nitrogen as the balance gas) were used as the target gases to assess the sensor performance. A detailed comparison of the three measurement schemes is reported. Here, atmospheric C 2 H 6 measurements on the Rice University campus and a field test at a compressed natural gas station in Houston, TX, were conducted to evaluate the performance of the sensor system as a robust and reliable field-deployable sensor system.
Highlights: • Biogas can be upgraded to create biomethane, a substitute to natural gas. • Biogas upgrading was applied to landfills and anaerobic digestors in 3 countries. • Up to 0.6% of a country’s consumption of natural gas could be replaced by biomethane. • Italy could save 46% of the national CO{sub 2} emissions attributed to the waste sector. • Scenarios were created to increase biomethane production. - Abstract: Biogas is rich in methane and can be further purified through biogas upgrading technologies, presenting a viable alternative to natural gas. Landfills and anaerobic digestors treating municipal solid waste are a large source of such biogas. They therefore offer an attractive opportunity to tap into this potential source of natural gas while at the same time minimizing the global warming impact resulting from methane emissions in waste management schemes (WMS) and fossil fuel consumption reduction. This study looks at the current municipal solid waste flows of Spain, Italy, and Austria over one year (2009), in order to determine how much biogas is generated. Then it examines how much natural gas could be substituted by using four different biogas upgrading technologies. Based on current waste generation rates, exploratory but realistic WMS were created for each country in order to maximize biogas production and potential for natural gas substitution. It was found that the potential substitution of natural gas by biogas resulting from the current WMS seems rather insignificant: 0.2% for Austria, 0.6% for Italy and 0.3% for Spain. However, if the WMS is redesigned to maximize biogas production, these figures can increase to 0.7% for Austria, 1% for Italy and 2% for Spain. Furthermore, the potential CO{sub 2} reduction as a consequence of capturing the biogas and replacing fossil fuel can result in up to a 93% reduction of the annual national waste greenhouse gas emissions of Spain and Italy.
A mid-infrared ethane (C 2 H 6 ) sensor based on a wavelength modulation spectroscopy (WMS) technique was developed using a thermoelectrically cooled (TEC), continuous-wave (CW) interband cascade laser (ICL) emitting at 3.34 μm and a dense multi-pass gas cell (MPGC, 17 × 6.5 × 5.5 cm 3 ) with a 54.6 m optical path length. A compact optical sensor system with a physical size of 35.5 × 18 × 12.5 cm 3 was designed and constructed. An ICL was employed for targeting a strong C 2 H 6 line at 2996.88 cm -1 at <100 Torr gas pressure in the fundamental absorption band of C 2 H 6 . The sensor performance, including the minimum detection limit (MDL) and the stability were improved by reducing the effect of laser power drift by means of the 2f/1f-WMS technique. A MDL of ~1.2 parts per billion (ppbv) for 2f-WMS and ~1.0 ppbv for 2f/1f-WMS were achieved, respectively, with a measurement time of 4 s. The MDL was further improved from 299 pptv (@108 s for 2f-WMS) to 239 pptv (@208 s for 2f/1f-WMS), based on an Allan deviation analysis.The rise time (@0 → 100 ppbv) and fall time (@100 → 0 ppbv) were determined to be ~64 s and ~48 s,respectively, at a gas pressure of <100 Torr for the C 2 H 6 sensor operation.
Monitoring services play a crucial role in the day-to-day operation of distributed computing systems. The ATLAS Experiment at LHC uses the Production and Distributed Analysis workload management system (PanDA WMS), which allows a million computational jobs to run daily at over 170 computing centers of the WLCG and opportunistic resources, utilizing 600k cores simultaneously on average. The BigPanDA monitor is an essential part of the monitoring infrastructure for the ATLAS Experiment that provides a wide range of views, from top-level summaries to a single computational job and its logs. Over the past few years of the PanDA WMS advancement in the ATLAS Experiment, several new components were developed, such as Harvester, iDDS, Data Carousel, and Global Shares. Due to its modular architecture, the BigPanDA monitor naturally grew into a platform where the relevant data from all PanDA WMS components and accompanying services are accumulated and displayed in the form of interactive charts and tables. Moreover the system has been adopted by other experiments beyond HEP. In this paper we describe the evolution of the BigPanDA monitor system, the development of new modules, and the integration process into other experiments.
Modern scientific workflows process massive amounts of data from diverse instruments and sensors, leveraging geographically distributed, heterogeneous compute and storage resources—from leadership-class systems to edge devices—connected by high-performance networks. The diversity of resources introduces challenges in harnessing their full potential, with resilience issues arising across applications, system software, networks, storage, and hardware. Today, workflow management systems (WMS) coordinate the execution of computation and data management tasks across target resources. However, WMS’s centralized nature makes them vulnerable to faults and scalability issues that may result in failures of entire computational campaigns. In conclusion, this paper introduces a novel agentic framework for workflow management, fully distributing and decentralizing the WMS functions and modeling them as swarm intelligence agents infused with advanced artificial intelligence solutions and traditional distributed computing algorithms that can make coordinated decisions in the presence of failures of the underlying cyberinfrastructure.
A ppb-level formaldehyde (H 2 CO) sensor was developed using a thermoelectrically cooled (TEC), continuous-wave (CW) room temperature interband cascade laser (ICL) emitting at 3.59 μm and a miniature dense pattern multipass gas cell with >50 m optical path length. Performance of the sensor was investigated with two measurement schemes: direct absorption (DAS) and wavelength modulation spectroscopy (WMS). With an integration time of less than 1.5 second, a detection limit of ~3 ppbv for H 2 CO measurement with precision of 1.25 ppbv for DAS and 0.58 ppbv for WMS, respectively, was achieved without zero air based background subtraction. An Allan-Werle variance analysis indicated that the precisions can be further improved to 0.26 ppbv @ 300s for DAS and 69 pptv @ 90 s for WMS, respectively. Finally, a side-by-side comparison between two measurement schemes is also discussed in detail.
The North Railroad Avenue Plume (NRAP) Superfund site in New Mexico, USA exemplifies successful chlorinated solvent bioremediation. NRAP was the result of leakage from a dry-cleaning that operated for 37 years. The presence of tetrachloroethene biodegradation byproducts, organohalide respiring genera (OHRG), and reductive dehalogenase (rdh) genes detected in groundwater samples indicated that enhanced reductive dechlorination (ERD) was the remedy of choice. This was achieved through biostimulation by mixing emulsified vegetable oil into the contaminated aquifer. This report combines metagenomic techniques with site monitoring metadata to reveal new details of ERD. DNA extracts from groundwater samples collected prior to and at four, 23 and 39 months after remedy implementation were subjected to whole metagenome sequencing (WMS) and 16S rRNA gene amplicon (16S) analyses. The response of the indigenous NRAP microbiome to ERD protocols is consistent with results obtained from microcosms, dechlorinating consortia, and observations at other contaminated sites. WMS detects three times as many phyla and six times as many genera as 16S. Both techniques reveal abundance changes in Dehalococcoides and Dehalobacter that reflect organohalide form and availability. Methane was not detected before biostimulation but appeared afterwards, corresponding to an increase in methanogenic Archaea. Assembly of WMS reads produced scaffolds containing rdh genes from Dehalococcoides, Dehalobacter, Dehalogenimonas, Desulfocarbo, and Desulfobacula. Anaerobic and aerobic cometabolic organohalide degrading microbes that increase in abundance include methanogenic Archaea, methanotrophs, Dechloromonas, and Xanthobacter, some of which contain hydrolytic dehalogenase genes. Aerobic cometabolism may be supported by oxygen gradients existing in aquifer microenvironments or by microbes that produce O 2 via microbial dismutation. The NRAP model for successful ERD is consistent with the established pathway and identifies new taxa and processes that support this syntrophic process. This project explores the potential of metagenomic tools (MGT) as the next advancement in bioremediation.
The question of whether or not consolidated interim storage of commercial spent nuclear fuel (SNF) should be part of the federal waste management system as an intermediate step before permanent disposal has been debated for more than four decades. This paper summarizes an evaluation of the cost implications of incorporating a consolidated interim storage facility (ISF) into the waste management system (WMS). In this study, the order-of-magnitude estimates of total system costs were calculated and tabulated. The analyzed scenarios involve shipment of SNF from reactors in dual-purpose storage and transportation canisters (DPCs) currently being used by utilities for dry storage at reactor sites. A number of pertinent conclusions can be drawn from this evaluation, including: - Delay in repository availability increases total system costs. Any delay in opening a repository increases total system costs, regardless of whether the system has an ISF or not. This is due to the increased cost associated with an extended duration for storage, whether at multiple independent spent fuel storage installations (ISFSIs) or at an ISF, until waste can be disposed of.- There is a potential total system lifecycle cost avoidance in realistic scenarios with an ISF when compared to scenarios with no ISF. However, most of the cost avoidance occurs several decades after the ISF is opened. The total WMS cost differential over the long term is mainly attributed to the reduced operational costs of storing the fuel in a consolidated facility rather than at individual reactor sites. - Earlier establishment of an ISF allows for more avoidance of post-shutdown at-reactor storage costs for any repository opening date. An ISF allows earlier acceptance of fuel from reactors, which reduces at-reactor costs from a total system perspective. - Transportation costs have little impact on a WMS with or without an ISF. These impacts range from 3-11% of the total cost in all scenarios. Therefore, transporting the fuel twice does not appear to be a significant cost concern driver relative to other system costs. In conclusion, designing, licensing, and constructing an ISF will require a large near-term financial investment. However, reduced annual operating and maintenance costs for an integrated waste management system with an ISF, compared to a system without an ISF, could eventually result in system-wide (integrated) cost avoidance due to reductions in at-reactor storage costs in the long term. The largest cost avoidances would not occur for several decades, so assumptions about inflation, escalation, and discount rates will have a significant effect on potential economic impacts of an ISF. It should be noted that other benefits associated with the investment of an ISF-such as earlier removal of SNF from shutdown reactor sites, earlier prospects for site re-utilization, and additional overall integrated waste management system flexibility-were not addressed in this study. (authors)
An EPR experiment is studied where each particle within the entangled pair undergoes a few weak measurements (WMs) along some pre-set spin orientations, with the outcomes individually recorded. Then the particle undergoes one strong measurement along an orientation chosen at the last moment. Bell-inequality violation is expected between the two final measurements within each EPR pair. At the same time, statistical agreement is expected between these strong measurements and the earlier weak ones performed on that pair. A contradiction seemingly ensues: (i) Bell’s theorem forbids spin values to exist prior to the choice of the orientation measured; (ii) A weak measurement is not supposed to determine the outcome of a successive strong one; and indeed (iii) Almost no disentanglement is inflicted by the WMs; and yet (iv) The outcomes of weak measurements statistically agree with those of the strong ones, suggesting the existence of pre-determined values, in contradiction with (i). Although the conflict can be solved by mere mitigation of the above restrictions, the most reasonable resolution seems to be that of the Two-State-Vector Formalism (TSVF), namely, that the choice of the experimenter has been encrypted within the weak measurement’s outcomes, even before the experimenters themselves know what their choice will be.
The term “scientific workflow” has evolved over the last two decades to encompass a broad range of compositions of interdependent compute tasks and data movements. It has also become an umbrella term for processing in modern scientific applications. Today, many scientific applications can be considered as workflows made of multiple dependent steps, and hundreds of workflow systems have been developed to manage and run these scientific workflows. However, no turnkey solution has emerged from the field to address the diversity of scientific processes and the infrastructure on which they are supposed to be implemented. Instead, new research problems requiring the execution of scientific workflows with some novel feature often lead to the development of an entirely new workflow system. A direct consequence of this situation is that many existing workflow management systems (WMSs) share some salient features, offer similar functionalities, and can manage the same categories of workflows but at the same time also have some distinct capabilities that can be important for specific applications. This situation makes researchers who develop workflows face the complex question of selecting a WMS. This selection can be driven by technical considerations, to find the system that is the most appropriate for their application and for the computing and storage resources available to them, or other factors such as reputation, adoption, strong community support, or long-term sustainability. To address this problem, a group of WMS developers and practitioners joined their efforts to produce a community-based terminology of WMSs. This paper summarizes their findings and introduces this new terminology to characterize WMSs. Furthermore, this terminology is composed of fives axes: workflow structure and characteristics, composition, orchestration, data management, and metadata capture. Each axis comprises several concepts that capture the prominent features of WMSs. Based on this terminology, this paper also presents a classification of 23 existing WMSs according to the proposed axes and terms.
The κ-opioid receptor (KOR) has emerged as an attractive drug target for pain management without addiction, and biased signaling through particular pathways of KOR may be key to maintaining this benefit while minimizing side-effect liabilities. As for most G protein-coupled receptors (GPCRs), however, the molecular mechanisms of ligand-specific signaling at KOR have remained unclear. To better understand the molecular determinants of KOR signaling bias, we apply structure determination, atomic-level molecular dynamics (MD) simulations, and functional assays. We determine a crystal structure of KOR bound to the G protein-biased agonist nalfurafine, the first approved KOR-targeting drug. We also identify an arrestin-biased KOR agonist, WMS-X600. Using MD simulations of KOR bound to nalfurafine, WMS-X600, and a balanced agonist U50,488, we identify three active-state receptor conformations, including one that appears to favor arrestin signaling over G protein signaling and another that appears to favor G protein signaling over arrestin signaling. These results, combined with mutagenesis validation, provide a molecular explanation of how agonists achieve biased signaling at KOR.
The PanDA WMS - Production and Distributed Analysis Workload Management System - has been developed and used by the ATLAS experiment at the LHC (Large Hadron Collider) for all data processing and analysis challenges. BigPanDA is an extension of the PanDA WMS to run ATLAS and non-ATLAS applications on Leadership Class Facilities and supercomputers, as well as traditional grid and cloud resources. The success of the BigPanDA project has drawn attention from other compute intensive sciences such as biology. In 2017, a pilot project was started between BigPanDA and the Blue Brain Project (BBP) of the Ecole Polytechnique Federal de Lausanne (EPFL) located in Lausanne, Switzerland. This proof of concept project is aimed at demonstrating the efficient application of the BigPanDA system to support the complex scientific workflow of the BBP, which relies on using a mix of desktop, cluster and supercomputers to reconstruct and simulate accurate models of brain tissue.
The Large Hadron Collider (LHC), operating at the international CERN Laboratory in Geneva, Switzerland, is leading Big Data driven scientific explorations. Experiments at the LHC explore the fundamental nature of matter and the basic forces that shape our universe, and were recently credited for the discovery of a Higgs boson. ATLAS and ALICE are the largest collaborations ever assembled in the sciences and are at the forefront of research at the LHC. To address an unprecedented multi-petabyte data processing challenge, both experiments rely on a heterogeneous distributed computational infrastructure. The ATLAS experiment uses PanDA (Production and Data Analysis) Workload Management System (WMS) for managing the workflow for all data processing on hundreds of data centers. Through PanDA, ATLAS physicists see a single computing facility that enables rapid scientific breakthroughs for the experiment, even though the data centers are physically scattered all over the world. The scale is demonstrated by the following numbers: PanDA manages O(10 2 ) sites, O(10 5 ) cores, O(10 8 ) jobs per year, O(10 3 ) users, and ATLAS data volume is O(10 17 ) bytes. In 2013 we started an ambitious program to expand PanDA to all available computing resources, including opportunistic use of commercial and academic clouds and Leadership Computing Facilities (LCF). The project titled 'Next Generation Workload Management and Analysis System for Big Data' (BigPanDA) is funded by DOE ASCR and HEP. Extending PanDA to clouds and LCF presents new challenges in managing heterogeneity and supporting workflow. The BigPanDA project is underway to setup and tailor PanDA at the Oak Ridge Leadership Computing Facility (OLCF) and at the National Research Center "Kurchatov Institute" together with ALICE distributed computing and ORNL computing professionals. Our approach to integration of HPC platforms at the OLCF and elsewhere is to reuse, as much as possible, existing components of the PanDA system. Finally, we will present our current accomplishments with running the PanDA WMS at OLCF and other supercomputers and demonstrate our ability to use PanDA as a portal independent of the computing facilities infrastructure for High Energy and Nuclear Physics as well as other data-intensive science applications.
The PanDA (Production and Distributed Analysis) workload management system (WMS) was developed to meet the scale and complexity of LHC distributed computing for the ATLAS experiment. While PanDA currently distributes jobs to more than 100,000 cores at well over 100 Grid sites, the future LHC data taking runs will require more resources than Grid computing can possibly provide. To alleviate these challenges, ATLAS is engaged in an ambitious program to expand the current computing model to include additional resources such as the opportunistic use of supercomputers. We will describe a project aimed at integration of PanDA WMS with Titan supercomputer at Oak Ridge Leadership Computing Facility (OLCF). The current approach utilizes a modified PanDA pilot framework for job submission to Titan’s batch queues and local data management, with light-weight MPI wrappers to run single threaded workloads in parallel on Titan’s multi-core worker nodes. It also gives PanDA new capability to collect, in real time, information about unused worker nodes on Titan, which allows precise definition of the size and duration of jobs submitted to Titan according to available free resources. This capability significantly reduces PanDA job wait time while improving Titan’s utilization efficiency. This implementation was tested with a variety of Monte-Carlo workloads on Titan and is being tested on several other supercomputing platforms.