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At least 199 records · Page 11

Analysis Ready Data in Analytics Optimized Data Stores for Analysis of Big Earth Data in the Cloud

Cloud computing offers the possibility of making the analysis of Big Data approachable for a wider community due to affordable access to computing power, an ecosystem of usable tools for parallel processing, and migration of many large datasets to archives in the cloud, allowing data-proximal computing. Generally, data analysis acceleration in the cloud comes from running multiple nodes in a split-combine-apply strategy. Data systems such as the Earth Observing System Data and Information System are in a position to "pre-split" the data by storing them in a data store that is optimized for data parallel computing, i.e., an Analytics-Optimized Data Store (AODS). A variety of approaches to AODS are possible, from highly scalable databases to scalable filesystems to data formats optimized for cloud access (e.g., zarr and cloud-optimized datasets), with the optimal choice dependent on both the types of analysis and the geospatial structure of the data. A key question is how much preprocessing of the data to do, both before splitting and as the first part of the apply step. Again, the geospatial structure of the data and the analysis type influence the decision, with the added complexity of the user type. Trans-disciplinary users who are not well-versed in the nuances of quality-filtering and georeferencing of remote sensing orbit/swath/scene data tend to ask for more highly processed data, relying on the data provider to make sensible decisions on preprocessing parameters. (This accounts for the popularity of "Level 3" gridded data, despite the lower spatial resolution it provides.) In this case, data can be preprocessed before the split, resulting in higher performance in the rest of the "apply" step, which can be transformative for use cases such as interactive data exploration at scale. Discipline researchers who are experienced with remote sensing data often prefer more flexibility in customizing the preprocessing data into Analysis Ready Data, resulting in more need for on-the-fly preprocessing.

Lynnes, Christopher↗

A Misload Analysis Methodology Supporting Criticality Analysis of Spent Nuclear Fuel Canisters Using As-Loaded Configurations

This paper presents an assembly misload analysis methodology developed to support criticality safety analysis of spent nuclear fuel (SNF) dual-purpose canisters (DPCs) using as-loaded configurations. The misload analysis approach is based on Interim Staff Guidance 8 “Burnup Credit in the Criticality Safety Analyses of PWR Spent Fuel in Transportation and Storage Casks” (ISG 8 rev. 3), but extended to support as-loaded configurations. The two misload scenarios analyzed included; (1) the correct assemblies are selected from the pool but placed incorrectly into the most reactive configuration inside the canister, and (2) the incorrect, most reactive assembly/assemblies in the pool is/are placed into the most reactive position(s) in the canister. Results from this misload analysis approach can be combined with misload probability to support criticality safety assessment of SNF during storage, transportation, and disposal. The misload analysis has been applied to 67 loaded DPCs at two sites using a disposal scenario. The analyzed sites include both PWR and BWR reactors and two canister variants—MPC-32 and MPC-68.

Liljenfeldt, Henrik↗

Real-Time XFEL Data Analysis at SLAC and NERSC: a Trial Run of Nascent Exascale Experimental Data Analysis

X-ray scattering experiments using Free Electron Lasers (XFELs) are a powerful tool to determine the molecular structure and function of unknown samples (such as COVID-19 viral proteins). XFEL experiments are a challenge to computing in two ways: i) due to the high cost of running XFELs, a fast turnaround time from data acquisition to data analysis is essential to make informed decisions on experimental protocols; ii) data collection rates are growing exponentially, requiring new scalable algorithms. Here we report our experiences analyzing data from two experiments at the Linac Coherent Light Source (LCLS) during September 2020. Raw data were analyzed on NERSC's Cori XC40 system, using the Superfacility paradigm: our workflow automatically moves raw data between LCLS and NERSC, where it is analyzed using the software package CCTBX. We achieved real time data analysis with a turnaround time from data acquisition to full molecular reconstruction in as little as 10 min -- sufficient time for the experiment's operators to make informed decisions. By hosting the data analysis on Cori, and by automating LCLS-NERSC interoperability, we achieved a data analysis rate which matches the data acquisition rate. Furthermore, completing data analysis with 10 mins is a first for XFEL experiments and an important milestone if we are to keep up with data collection trends.

Blaschke, Johannes P.↗

X-ray diffraction, differential scanning calorimetry and evolved gas analysis of aged plutonium tetrafluoride (PuF4)

A 30 year-old PuF4 sample consisting of brown powder (PuF4-b) and pink granules (PuF4-p) was analyzed. X-ray difraction shows the bulk is comprised of three compounds: PuF4, PuO2, and PuF4·1.6H2O. Broadening of PuF4 XRD peaks suggests possible a-damage. After annealing at 650 °C, crystalline PuF4 and PuO2 remain. Thermogravimetric analysis and diferential scanning calorimetry—with simultaneous evolved gas analysis—of the separated PuF4-p and PuF4-b components reveal a distinct sequence of reactions. Dehydration occurs between~90 and 300 °C. Exothermic annealing of the a-damage occurs in two stages: at 350–355 °C and at 555–558 °C. Hydrofuoric acid, fuorine and helium desorb during the frst exotherm. Above 700 °C, PuF4 reacts with PuO2, resulting in oxygen release and mass loss.

PuF4, dsc, differential scanning calorimetry, plut↗

Multivariate analysis of gamma spectra to characterize used nuclear fuel

Abstract—The Multi-Isotope Process (MIP) Monitor provides an efficient approach to monitoring the process conditions in used nuclear fuel reprocessing facilities to support process verification and validation. The MIP Monitor applies multivariate analysis to gamma spectroscopy of reprocessing streams in order to detect small changes in the gamma spectrum, which may indicate changes in process conditions. This research extends the MIP Monitor by characterizing a used fuel sample after initial dissolution according to the type of reactor of origin (pressurized or boiling water reactor), initial enrichment, burn up, and cooling time. Simulated gamma spectra were used to develop and test three fuel characterization algorithms. The classification and estimation models employed are based on the partial least squares regression (PLS) algorithm. A PLS discriminate analysis model was developed which perfectly classified reactor type. Locally weighted PLS models were fitted on-the-fly to estimate continuous fuel characteristics. Burn up was predicted within 0.1% root mean squared percent error (RMSPE) and both cooling time and initial enrichment within approximately 2% RMSPE. This automated fuel characterization can be used to independently verify operator declarations of used fuel characteristics and inform the MIP Monitor anomaly detection routines at later stages of the fuel reprocessing stream to improve sensitivity to changes in operational parameters and material diversions.

Multivariate Analysis for Characterization of Used↗

Techno-economic Analysis of Novel PV Plant Designs for Extreme Cost Reductions

A techno-economic analysis is underway examining the cost and performance of future large-scale photovoltaic (PV) plant components, including bifacial modules, tandem modules, increased plant voltage architectures, and module-level power electronics. Integration of these components into PV plant designs is compared with current PV technologies based on levelized cost of electricity (LCOE). Baseline models are developed and validated against recorded PV plant performance data. Expected cost and performance data of future PV technologies are incorporated into the baseline models. An evolutionary algorithm is utilized to optimize PV plant configuration, technology combination, and LCOE. Furthermore, this paper focuses on the bifacial module analysis.

14 SOLAR ENERGY↗

Cost Effectiveness Analysis of Quasi-Static Wireless Power Transfer for Plug-In Hybrid Electric Transit Buses: Preprint

This study evaluates the costs and benefits associated with the use of a plug-in hybrid electric bus and determines the cost effectiveness relative to a conventional bus and a hybrid electric bus. A sensitivity sweep analysis was performed over a number of a different battery sizes, charging powers, and charging stations. The net present value was calculated for each vehicle design and provided the basis for the design evaluation. In all cases, given present day economic assumptions, the conventional bus achieved the lowest net present value while the optimal plug-in hybrid electric bus scenario reached lower lifetime costs than the hybrid electric bus. The study also performed parameter sensitivity analysis under low market potential assumptions and high market potential assumptions. The net present value of plug-in hybrid electric bus is close to that of conventional bus.

33 ADVANCED PROPULSION SYSTEMS↗

Online data analysis and reduction: An important co-design motif for extreme-scale computers

A growing disparity between supercomputer computation speeds and I/O rates means that it is rapidly becoming infeasible to analyze supercomputer application output only after that output has been written to a file system. Instead, data-generating applications must run concurrently with data reduction and/or analysis operations, with which they exchange information via high-speed methods such as interprocess communications. The resulting parallel computing motif, online data analysis and reduction (ODAR), has important implications for both application and HPC systems design. Here we introduce the ODAR motif and its co-design concerns, describe a co-design process for identifying and addressing those concerns, present tools that assist in the co-design process, and present case studies to illustrate the use of the process and tools in practical settings.

Data Analysis↗

Data for 3-Hydroxypropionic Acid Recovery from Fermentation Broth through Novel Downstream Processing: Technoeconomic Analysis

This study develops and validates a simplified, fully solvent-free downstream processing (DSP) strategy for high-purity recovery of 3-hydroxypropionic acid (3-HP) from real fermentation broth containing 62.3 g/L of 3-HP. Optimized activated carbon treatment achieved 98% color removal, while Amberlite IRA-67 was operated at pH 4.5 and 30 °C to minimize product loss. This is the first integrated demonstration of a fully solvent-free DSP enabling recovery of bio-based 3-HP as both a solid sodium salt and a concentrated aqueous solution, supported by techno-economic analysis. At lab scale, the process achieved 77.3% recovery of sodium 3-HP with 83.2% (w/w) purity and produced a 30% (w/v) aqueous solution. Techno-economic analysis yielded minimum selling prices of $0.551/kg for the solution and $0.892/kg for the salt, both below target thresholds for cost-competitive bio-acrylic acid production. Overall, these results demonstrate an efficient, scalable, and economically viable industrial pathway for 3-HP recovery.

Bioproducts↗

Interrelationship of Thermal Effects on Calcium Sulfate Dihydrate Casts Containing Borax and Kaolin: Differential Thermal Analysis (DTA), Thermogravimetric Analysis (TGA), and Contact Dilatometry

The core composition of gypsum wallboard is calcium sulfate dihydrate (CaSO 4 ·2H 2 O) with varying impurities, additives, or both. This study compares here two commercially calcined sources of hemihydrate (CaSO 4 ·½H 2 O) from a natural source and a synthetic by-product of flue gas desulfurization and neutralization to reagent grade hemihydrate. Two common ingredients, borax and kaolin, are mixed into a slurry with distilled water. The analysis supports the hypothesis that minor components in the cast have an effect on the high temperature performance of gypsum casts. The analysis is enhanced when the differential thermal analysis, thermogravimetric analysis, and dilatometry data are combined to study the changes in density versus heat flow. Specifically, the thermal performance is affected by (1) the impurities found in hemihydrate sources; (2) during the fluidization phase, the reaction of borax with free Ca ++ ions to form new borate salts that melt at lower temperatures; and (3) the intercalation of these and other ions with kaolin, providing thermal stability by reducing the formation of thermally active salts.

36 MATERIALS SCIENCE↗

Thermal-Mechanical Stress Analysis of PWR Pressure Vessel and Nozzles under Grid Load-Following Mode: Interim Report on the Effect of Cyclic Hardening Material Properties and Pre-existing Cracks on Stress Analysis Results

This report provides an update on an assessment of environmentally assisted fatigue for light water reactor components under extended service conditions. This report is a deliverable under the work package for environmentally assisted fatigue as part of DOE’s Light Water Reactor Sustainability Program. In a previous report (September 2015), we presented tensile and fatigue test data and related hardening material properties for 508 low-alloys steel base metal and other reactor metals. In this report, we present thermal-mechanical stress analysis of the reactor pressure vessel and its hot-leg and cold-leg nozzles based on estimated material properties. We also present results from thermal and thermal-mechanical stress analysis under reactor heat-up, cool-down, and grid load-following conditions. Analysis results are given with and without the presence of preexisting cracks in the reactor nozzles (axial or circumferential crack). In addition, results from validation stress analysis based on tensile and fatigue experiments are reported.

42 ENGINEERING↗

Irradiation Experiments and Thermal Analysis for Reactor System Design and Analysis at INL

Idaho National Laboratory (INL) is the nation's lead nuclear laboratory working to enhance reactor systems' safety, security, economics, and efficiency. Research and development (R&D) programs at INL support the current fleet of nuclear reactors for safer operation and newer reactors technology design, development, demonstration, and deployment. A major focus of INL's mission is the reactor system design and analysis supported by the irradiation experiments and thermal analysis of advanced and current-generation nuclear fuels and materials. The irradiation experiments and thermal analysis provide a deeper understanding of basic radiation damage processes that can determine the basis for performance improvements and verification of modeling assumptions. These experiments and analyses include experiment management: design, fabrication, characterization, irradiation, and post-irradiation examination. This research involves thermal, neutronic, and material investigation using the INL's Advanced Test Reactor (ATR) and Transient Reactor Test (TREAT) facilities. The results from these experiments and analysis are required to develop the regulatory basis for deploying new or modified fuels and materials. This seminar talk will also provide a general overview of the INL's research facilities, ongoing research programs, core capabilities, and opportunities for students and faculties.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Monitoring of Wind Turbine Gearbox Condition through Oil and Wear Debris Analysis: A Full-Scale Testing Perspective

Despite the wind industry's dramatic development during the past decade, it is still challenged by premature turbine subsystem/component failures, especially for turbines rated above 1 MW. Because a crane is needed for each replacement, gearboxes have been a focal point for improvement in reliability and availability. Condition monitoring (CM) is a technique that can help improve these factors, leading to reduced turbine operation and maintenance costs and, subsequently, lower cost of energy for wind power. Although technical benefits of CM for the wind industry are normally recognized, there is a lack of published information on the advantages and limitations of each CM technique confirmed by objective data from full-scale tests. This article presents first-hand oil and wear debris analysis results obtained through tests that were based on full-scale wind turbine gearboxes rated at 750 kW. The tests were conducted at the 2.5-MW dynamometer test facility at the National Wind Technology Center at the National Renewable Energy Laboratory. The gearboxes were tested in three conditions: run-in, healthy, and damaged. The investigated CM techniques include real-time oil condition and wear debris monitoring, both inline and online sensors, and offline oil sample and wear debris analysis, both onsite and offsite laboratories. The reported results and observations help increase wind industry awareness of the benefits and limitations of oil and debris analysis technologies and highlight the challenges in these technologies and other tribological fields for the Society of Tribologists and Lubrication Engineers and other organizations to help address, leading to extended gearbox service life.

17 WIND ENERGY↗

Catalyst Revised: Rethinking the ParaView in Situ Analysis and Visualization API

As in situ analysis goes mainstream, ease of development, deployment, and maintenance becomes essential, perhaps more so than raw capabilities. In this paper, we present the design and implementation of Catalyst, an API for in situ analysis using ParaView, which we refactored with these objectives in mind. Furthermore, our implementation combines design ideas from in situ frameworks and HPC tools like Ascent and MPICH.

97 MATHEMATICS AND COMPUTING↗

Techno-Economic Analysis of Liquid Fuel Production from Woody Biomass via Hydrothermal Liquefaction (HTL) and Upgrading

A series of experimental work was conducted to convert woody biomass to gasoline and diesel range products via hydrothermal liquefaction (HTL) and catalytic hydroprocessing. Based on the best available test data, a techno-economic analysis (TEA) was developed for a large scale woody biomass based HTL and upgrading system to evaluate the feasibility of this technology. In this system, 2000 dry metric ton per day woody biomass was assumed to be converted to bio-oil in hot compressed water and the bio-oil was hydrotreated and/or hydrocracked to produce gasoline and diesel range liquid fuel. Two cases were evaluated: a stage-of-technology (SOT) case based on the tests results, and a goal case considering potential improvements based on the SOT case. Process simulation models were developed and cost analysis was implemented based on the performance results. The major performance results included final products and co-products yields, raw materials consumption, carbon efficiency, and energy efficiency. The overall efficiency (higher heating value basis) was 52% for the SOT case and 66% for the goal case. The production cost, with a 10% internal rate of return and 2007 constant dollars, was estimated to be $1.29 /L for the SOT case and $0.74 /L for the goal case. The cost impacts of major improvements for moving from the SOT to the goal case were evaluated and the assumption of reducing the organics loss to the water phase lead to the biggest reduction in the production cost. Sensitivity analysis indicated that the final products yields had the largest impact on the production cost compared to other parameters. Plant size analysis demonstrated that the process was economically attractive if the woody biomass feed rate was over 1,500 dry tonne/day, the production cost was competitive with the then current petroleum-based gasoline price.

Techno-economic analysis, Biomass, Hydrothermal li↗

Stability analysis of nonlinear two-grid method for multigroup neutron diffusion problems

We present theoretical analysis of a nonlinear acceleration method for solving multigroup neutron diffusion problems. This method is formulated with two energy grids that are defined by (i) fine-energy groups structure and (ii) coarse grid with just a single energy group. The coarse-grid equations are derived by averaging of the multigroup diffusion equations over energy. The method uses a nonlinear prolongation operator. We perform stability analysis of iteration algorithms for inhomogeneous (fixed-source) and eigenvalue neutron diffusion problems. To apply Fourier analysis the equations of the method are linearized about solutions of infinite-medium problems. The developed analysis enables us to predict convergence properties of this two-grid method in different types of problems. Numerical results of problems in 2D Cartesian geometry are presented to confirm theoretical predictions.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗