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At least 649 records · Page 36

Kira: Processing Astronomy Imagery Using Big Data Technology

Scientific analyses commonly compose multiple single-process programs into a dataflow. An end-to-end dataflow of single-process programs is known as a many-task application. Typically, HPC tools are used to parallelize these analyses. In this work, we investigate an alternate approach that uses Apache Spark-a modern platform for data intensive computing-to parallelize many-task applications. We implement Kira, a flexible and distributed astronomy image processing toolkit, and its Source Extractor (Kira SE) application. Using Kira SE as a case study, we examine the programming flexibility, dataflow richness, scheduling capacity and performance of Apache Spark running on the Amazon EC2 cloud. By exploiting data locality, Kira SE achieves a 4.1× speedup over an equivalent C program when analyzing a 1TB dataset using 512 cores on the Amazon EC2 cloud. Furthermore, Kira SE on the Amazon EC2 cloud achieves a 1.8× speedup over the C program on the NERSC Edison supercomputer. A 128-core Amazon EC2 cloud deployment of Kira SE using Spark Streaming can achieve a second-scale latency with a sustained throughput of 800 MB/s. Our experience with Kira demonstrates that data intensive computing platforms like Apache Spark are a performant alternative for many-task scientific applications.

97 MATHEMATICS AND COMPUTING↗

Center for Energy Efficient Materials (CEEM) (Final Technical Report)

The mission of the Center for Energy Efficient Materials (CEEM) was to serve the Department of Energy and the nation as a center of excellence dedicated to advancing basic research in nano-structured materials and devices for applications to solar electricity, thermoelectric conversion of waste heat to electricity, and solidstate lighting. The foundation of CEEM was based on the unique capabilities of UCSB and its partner institutions to control, synthesize, characterize, model, and apply materials at the nanoscale for more efficient sustainable energy resources. This unique expertise was a key source of the synergy that unified the research of the Center. Although the Center’s focus was basic research, It’s longer-term objective has been to transfer new materials and devices into the commercial sector where they will have a substantial impact on the nation’s need for efficient sustainable energy resources. As one measure of the impact of the Center, two start-up companies were formed based on its research. In addition, Center participants published a total of 210 archival journal articles, of which 51 were exclusively sponsored by the DOE grant. The work of the Center was structured around four specific tasks: Organic Solar Cells, Solid-State Lighting, Thermoelectrics, and High Efficiency Multi-junction Photovoltaic devices. A brief summary of each follows – detailed descriptions are in Sections 4 & 5 of this report. Research supported through CEEM led to an important shift with respect to the choice of materials used for the fabrication of solution deposited organic solar cells. Solution deposition opens the opportunity to manufacture solar cells via economically-viable high throughput tools, such as roll to roll printing. Prior to CEEM, most organic semiconductors utilized for this purpose involved polymeric materials, which, although they can form thin films reliably, suffer from batch to batch variations due to the statistical nature of the chemical reactions that produce them. In response, the CEEM team developed well-defined molecular semiconductors that produce active layers with very high power conversion efficiencies, in other words they can convert a very high fraction of sunlight into useful electrical power. The fact that the semiconductor is formed from molecular species provides the basis for circumventing the unreliability of polymer counterparts and, as an additional bonus, allows one to attain much grater insight into the structure of the active layer. The latter is particularly important because efficient conversion is the result of a complex arrangement of two semiconductors that need to phase separate in a way akin to oil and water, but with domains that are described by nanoscale dimensions. CEEM was therefore able to provide deep insight into the influence of nanostructure, through the application of structural characterization tools and theoretical methods that describe how electrical charges migrate through the organic layer. Our research in light emitting diode (LED)-based solid state lighting (SSL) was directed at improving efficiency and reducing costs to enable the widespread deployment of economically-viable replacements for inefficient incandescent, halogen, and fluorescent-based lighting. Our specific focus was to advance the fundamental science and technology of light emitting diodes to both understand factors that limit efficiencies and to provide innovative and viable solutions to the current impediments. One of the main challenges we faced is the decrease in efficiency when LEDs are driven harder to increase light output---the so called “droop” effect. It requires large emitting surfaces to reach a desired optical output, and necessitates the use of costly heat sinks, both of which increase the cost. We successfully reduced droop by growing LED crystals having non-conventional orientations. As recognized by the award of the 2014 Nobel prize to the inventors of the nitride LEDs (one of whom was a member of CEEM), LEDs already have a large societal impact in both developed (leading to large energy savings) and developing countries (bringing light where there is no electrical grid). The improvements in efficiency sought after in the CEEM project are key to a further impact of solid state lighting by LEDs with a projected doubling in efficiency by year 2020. Direct generation of electricity from heat has enormous promise for beneficial use of waste heat. But practical power generation directly from heat requires understanding and development of new and improved materials that will be more efficient and rugged than today’s thermoelectric materials. To accomplish this goal CEEM has synthesized five distinct and promising new classes of thermoelectric materials: (a) nanoparticle arrays that are effective in maximizing electric power generation and reducing detrimental loss of heat; (b) nitride and (c) oxide thermal electric materials that are effective at high temperatures where much beneficial heat is available; (d) arrays of silicon nano-wires that integrate thermal electricity generation into silicon-based electronics and materials; and (e) chemically synthesized nanostructured compounds that are cost effective, earth abundant, and environmentally friendly. The further development of these thermoelectric sources of electricity could have revolutionary impact for society in the recovery of waste heat from sources such as power plants and automobile exhaust, where there could be significant associated energy saving. It could even, in the future, provide disruptive alternatives and replacements for today’s internal combustion engines and could enable improved all-electric propulsion by the heat from shipboard nuclear reactors. The High Efficiency Multi-junction Photovoltaics task was a UCSB/NREL collaboration which bonded sub-cells from two different compound semiconductors material systems to make high efficiency multijunction solar cells for concentrating photovoltaic applications thathave substantially higher efficiency than single substrate cells made of elemental semiconductors such as silicon. This task required the development of new cell bonding methods with excellent coupling of both photons and electrons between the sub-cells. To accomplish this, we developed (1) GaInN solar cells with enhanced performance by using quantum-well absorbers and front-surface optical texturing, (2) a hybrid "pillar-array" bond which uses an array of metal pillars for electrical coupling, and (3) a "hybrid moth-eye" optical coating which combines the benefits of nano-imprinted moth-eye coatings and traditional multilayer coatings. The technical effectiveness was assessed by measurement of the photovoltaic efficiency of solar cells made using these techniques; the ultrahigh efficiencies targeted by this work are of compelling economic value for concentrating photovoltaics.

14 SOLAR ENERGY↗

REPORTABLE RADIONUCLIDES IN DWPF SLUDGE BATCH 7A (MACROBATCH 8)

The Waste Acceptance Product Specifications (WAPS) 1.2 require that the waste producer 'shall report the curie inventory of radionuclides that have half-lives longer than 10 years and that are, or will be, present in concentrations greater than 0.05 percent of the total inventory for each waste type indexed to the years 2015 and 3115.' As part of the strategy to meet WAPS 1.2, the Defense Waste Processing Facility (DWPF) will report for each waste type all radionuclides that have half-lives longer than 10 years and contribute greater than 0.01 percent of the total curie inventory from the time of production through the 1100 year period from 2015 through 3115. The initial list of radionuclides to be reported is based on the design-basis glass identified in the Waste Form Compliance Plan (WCP) and Waste Form Qualification Report. However, it is required that the list be expanded if other radionuclides with half-lives greater than 10 years are identified that meet the 'greater than 0.01% of the curie inventory' criterion. Specification 1.6 of the WAPS, International Atomic Energy Agency Safeguards Reporting for High Level Waste (HLW), requires that the ratio by weights of the following uranium and plutonium isotopes be reported: U-233, U-234, U-235, U-236, and U-238; and Pu-238, Pu-239, Pu-240, Pu-241, and Pu-242. Therefore, the complete list of reportable radionuclides must also include these sets of U and Pu isotopes - and the U and Pu isotopic mass distributions must be identified. The DWPF receives HLW sludge slurry from Savannah River Site (SRS) Tank 40. For Sludge Batch 7a (SB7a), the waste in Tank 40 contained a blend of the heel from Sludge Batch 6 (SB6) and the Sludge Batch 7 (SB7) material transferred to Tank 40 from Tank 51. This sludge blend is also referred to as Macrobatch 8. Laboratory analyses of a Tank 40 sludge sample were performed to quantify the concentrations of pertinent radionuclides in the SB7a waste. Subsequently, radiological decay and in-growth were calculated over the time period from 2015 to 3115. This provided a basis for characterizing the radionuclide content of SB7a over time and for identifying the 'reportable radionuclides.' Details of the characterization methodology and the analytical results are the focus of this report. This work was performed at the request of the Waste Solidification Engineering Department of Savannah River Remediation, initiated via Technical Task Request (TTR) HLW-DWPF-TTR-2010-0031. A minor revision in the reporting requirements was requested via a subsequent email communication. The work was conducted in accordance with the protocols identified in Task Technical and Quality Assurance Plan SRNL-RP-2010-01218 and Analytical Study Plan SRNL-RP-2010-01219. All of the raw data related to this scope have been recorded in laboratory notebook SRNL-NB-2011-00061. The overall goal of this task was to characterize the radionuclide content of the SB7a waste sufficiently to meet the WAPS and DWPF reporting requirements. The specific objectives were: (1) Quantify the current concentrations of all radionuclides impacting (or potentially-impacting) the total curie content between calendar years 2011 and 3115. Also quantify the current concentrations of other radionuclides specifically requested in the TTR or required by the WAPS. (2) Calculate future concentrations of decayed and in-grown radionuclides impacting the total curie content between calendar years 2015 and 3115; (3) Identify as 'reportable' all radionuclides contributing {ge} 0.01% of the total curie content from 2015 to 3115 and having half-lives {ge} 10 years.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

TH-AB-207A-09: Tailoring TCM Schemes to a Task: Evaluating the Impact of Customized TCM Profiles On Detection of Lung Nodules in Simulated CT Lung Cancer Screening

Purpose: Recent work has shown that current TCM profile designs boost detection of low-contrast lung lesions in the lung apices, but yield reduced detection performance in the mid and lower lung regions relative to fixed tube current cases. This observed imbalance suggests that the TCM scheme might be tailored in new ways to maximize nodule detection throughout the entire lung. In this work, we begin a preliminary investigation into custom TCM profiles in an attempt to achieve uniform lesion detection throughout the extent of the lung. Methods: Low-contrast (25HU), 6mm nodules representing ground glass opacities were simulated at 1mm intervals over the length the lungs in a voxelized model of the XCAT phantom, one nodule per lung, per simulated scan. Voxel values represented attenuation values at 80keV. CT projection data was created by simulating a finite focal spot and using Joseph’s method for forward projection; scanner geometry was that of the Siemens Sensation 64 and the X-ray source was simulated as an 80keV monochromatic beam. Noise realizations were created using Poisson statistics, a realistic bowtie filter and varying tube current. 500 noise realizations were created for the custom TCM designs. All reconstruction was done with FreeCT-wFBP. An SKE/BKE task was used in conjunction with a 2D Hotelling Observer to calculate area-under-the-curve (AUC) as a proxy for “detectability.” AUC was plotted as a function of nodule Z-location to create a “detectability map.” The detectability map for the custom TCM curve was qualitatively assessed relative to previous results for the fixed TC and clinical TCM cases for uniformity. Results: Detection uniformity was improved throughout the mid and lower lungs, however detection remained disproportionately high in the upper lung region. Conclusion: Detection uniformity was improved with a custom TC profile. Future work will incorporate an analytic, task-specific approach to optimize the TC scheme for nodule detection. J. Hoffman: Part-time intern, Toshiba Medical Research Institute; M. McNitt-Gray: Institutional research agreement, Siemens Healthcare; Past recipient, research grant support, Siemens Healthcare; Consultant, Toshiba America Medical Systems; Consultant, Samsung Electronics; F. Noo: Institutional research agreement, Siemens Healthcare; Receives research funding from Siemens Healthcare.

60 APPLIED LIFE SCIENCES↗

Gasification of Coal and Biomass: The Route to Net-Negative-Carbon Power and Hydrogen

One promising process that is a candidate for meeting the goals of the US Department of Energy’s 21st Century Power Plant initiative is to gasify a mixture of coal and biomass to yield a syngas, which can have CO2 removed and then be used to produce hydrogen as well as an off-gas that can be used to flexibly produce power. This concept would overall be carbon net-negative and readily meet the 21st Century Power Plant initiative targets of smaller scale MW generation, high ramp rates and turndown, feedstock flexibility, and high efficiency—at a reasonable cost. Moreover, adding the large-scale production of “ultra-green” hydrogen yields a system tailored for the coming hydrogen economy, providing long-term energy storage and an attractive co-product for sale. The objective of the work being led by the Electric Power Research Institute, Inc. (EPRI), with support by Bechtel Corporation (Bechtel), Gas Technology Institute (GTI), Hamilton Mauer International, Inc. (HMI), Nebraska Public Power District (NPPD), NexantECA, Inc. (Nexant), and Wärtsilä, is to perform a front-end design and engineering (FEED) study on an oxygen-blown gasification system coupled with water-gas shift, pre-combustion CO2 capture, and pressure-swing adsorption working off a coal/biomass mix to yield high-purity hydrogen and a fuel off-gas that can generate power. Several designs are being considered that will be capable of producing 50 MW net from a flexible generator, over 8500 kg/hr of hydrogen, and net-negative CO2 emissions, at an efficiency of 50% net HHV. The plant would be hosted at an NPPD site, where opportunities for enhanced oil recovery and sequestration have been investigated and the need for low-carbon power and hydrogen is imminent. The principal biomass to be used is corn stover—prevalent in Nebraska where the plant will be located—mixed with Powder River Basin (PRB) coal, necessitating a gasifier that can use this feedstock and be flexible to allow other types. Waste plastics will also be reviewed for use. Two oxygen-blown gasifiers have been identified as candidates that have done testing with biomass including corn stover: the GTI gasifier—a high-pressure, fluidized-bed type—and HMI’s, a lower pressure moving-bed type. Both have relative advantages that are being investigated in the Phase I design study, with a resultant down select of one system for which the FEED will be performed in Phase II. The technical tasks for the proposed project are: • Design Development: Completion of design activities necessary to provide inputs for the FEED study. Multiple design cases will be assessed with the selection of the optimal one for the FEED. • Investment Case Preparation: Development of the draft investment case for the proposed process with business cases performed for the proposed host site and two other locations. • Host Site Selection: Evaluation of the two potential host sites within NPPD’s portfolio to select the preferred candidate based on technical, economic, and environmental considerations. • Environmental Information Volume (EIV) Development: Completion of the EIV for the host site. • FEED Study: Completion of a FEED study based on the design selected in Phase I. A Greenhouse Gas Life Cycle Analysis will also be performed for the process. • Update Investment Case: Finalization of the investment case based on findings from the FEED. The advantages of the proposed project are significant. Having an engaged U.S. power utility willing to provide a host site that will produce energy from coal plus a deep and experienced team is critical; the process meets all the goals of DOE’s 21st Century Power Plant initiative at an estimated total plant cost of ~$880M and a production cost of hydrogen of ~$2/kg-H2 while producing net-negative carbon power. If developed, this process has real commercial potential in the United States—supported by EPRI’s initial review of the considerable interest from selected U.S. utilities—and elsewhere around the globe. The process has fewer environmental hurdles compared to other concepts, lowering regulatory and protest risks—providing a pathway to preserving the viability of a critical indigenous energy source by transforming its use to match a changing world. This presentation will outline the motivation for the effort, summarize project plans, work completed to date, results of the Design Development task, and detailed work scope for the remainder of the project.

01 COAL, LIGNITE, AND PEAT↗

Performance-Aligned LLMs for Generating Fast HPC Code

Optimizing scientific software is a difficult task because codebases are often large and complex, and performance can depend upon several factors including the algorithm, its implementation, and hardware among others. Causes of poor performance can originate from disparate sources and be difficult to diagnose. Recent years have seen a multitude of work that use large language models (LLMs) to assist in software development tasks. However, these tools are trained to model the distribution of code as text, and are not specifically designed to understand performance aspects of code. In this work, we introduce a reinforcement learning based methodology to align the outputs of code LLMs with performance. This allows us to build upon the current code modeling capabilities of LLMs and extend them to generate better performing code. Here, we demonstrate that our fine-tuned model improves the expected speedup of generated code over base models for a set of benchmark tasks from 0.9 to 1.6 for serial code and 1.9 to 4.5 for OpenMP parallel code.

Computer science↗

Effect of Catalyst Pretreatment on Methane Conversion under Microwave-assisted and Conventional Thermal Methods

The presentation was delivered from work performed in NETL's Upcycling of Associated Natural Gas FWP Task 4 Benzene, Toluene, Xylene Synthesis via Microwave-assisted catalyst. The objective of this project is to develop a modular, microwave-assisted reactor to upcycle flare gas into valuable chemicals. The presentation discusses important work researchers have performed to compare the pre-treatment of a benchmark Mo/ZSM-5 catalyst under microwaves to traditional thermal heating. Pre-treatment is required to enable to catalyst to produce benzene. This study provided insights into how the exposure impacts the structure and activity of the catalyst and will be used to help design better catalysts.

Abdelsayed, Victor↗

A comparative analysis of numerical approaches for the description of gas flow in clay-based repository systems: From a laboratory to a large-scale gas injection test

There is nowadays a consensus among many countries that geological disposal is a favourable solution for the long-term management. Although different host formations and different barrier systems are under consideration around the world, clay-based materials form an important component for waste isolation in most national programmes. Hence, a good comprehension of the effect of gas flow on the hydro-mechanical behaviour of clay-based soils is essential, both at laboratory and field scale. Task B under the international cooperative project DECOVALEX-2023 has recently shown that, after some enhancement, models can be employed to reproduce laboratory scale tests, even with different sample geometries 37 . However, further work is required to understand whether they can be applied to simulate a large-scale experiment. Up-scaling of models for the advective transport of gas through clay-based low permeable material presents a number of problems related to the difficulty in obtaining consistent hydrogeological parameters and constitutive relationships at both laboratory and field scale. Based on a unique dataset from a large-scale gas injection test (Lasgit) performed at the Äspö Hard Rock Laboratory (Sweden), Task B within DECOVALEX-2023 has explored the refinement of these numerical strategies applied to the simulation of gas flow. Work performed within the task reveals that codes do not need to be substantially modified from the laboratory models to reproduce full-scale tests: indeed, model parameters calibrated and validated at laboratory scale have been applied to predict field scale gas flow at Lasgit, including peak gas pressure and injected cumulative gas volume. By means of (1) the introduction of interfaces between blocks to reflect the experimental configuration and the (2) adjustment of some parameters (e.g., higher permeability), the updated models are able to represent most of the key features observed in the experimental data, even at a large scale.

Tamayo-Mas, E↗

Recovery Act: Electrochromic Glazing Technology: Improved Performance, Lower Price (Final Report)

The growing dependency of the US on energy imports and anticipated further increases in energy prices reinforce the concerns about meeting the energy demand in the future and one element of a secure energy future is conservation. It is estimated that the buildings sector represents 40% of the US's total energy consumption. And buildings produce as much as one third of the greenhouse gas emissions primarily through fossil fuel usage during their operational phase. A significant fraction of this energy usage is simply due to inefficient window technology. Electrochromic (EC) windows allow electronic control of their optical properties so that the transparency to light can be adjusted from clear to dark. This ability to control the amount of solar energy allowed into the building can be advantageously used to minimize lighting, heating and air conditioning costs. Currently, the penetration of EC windows into the marketplace is extremely small, and consequently there is a huge opportunity for energy savings if this market can be expanded. In order to increase the potential energy savings it is necessary to increase the quantity of EC windows in operation. Additionally, any incremental improvement in the energy performance of each window will add to the potential energy savings. The overall goals of this project were therefore to improve the energy performance and lower the cost of dynamic (EC) smart windows for residential and commercial building applications. This project is obviously of benefit to the public by addressing two major areas: lowering the cost and improving the energy performance of EC glazings. The high level goals for these activities were: (i) to improve the range between the clear and the tinted state, (ii) reduce the price of EC windows by utilizing lower cost materials, (iii) lowering the U-Value, and (iv) ensure the proposed changes have no detrimental effect to the proven durability of the window. SAGE Electrochromics Inc. is the only company in the US which has a track record of producing EC windows, and presently has a small operational factory in Faribault MN which is shipping products throughout the world. There is a much larger factory currently under construction close by. This project was targeted specifically to address the issues outlined above, with a view to implementation on the new high volume manufacturing facility. Each of the Tasks which were addressed in this project is relatively straightforward to implement in this new facility and so the benefits of the work will be realized quickly. The research described here has helped to understand and provide solutions to several interesting and previously unresolved issues of the technology as well as make progress in areas which will have a significant impact on energy saving. In particular several materials improvements have been made, and tasks related to throughput and yield improvements have been completed. All of this has been accomplished without any detrimental effect on the proven durability of the SageGlass EC device. The project was divided into four main areas: 1. Improvement of the Properties of the EC device by material enhancements (Task 2); 2. Reduce the cost of production by improving the efficiency and yields of some key manufacturing processes (Task 3); 3. Further reduce the cost by significant modifications to the structure of the device (Task 4); 4. Ensure the durability of the EC device is not affected by any of the changes resulting from these activities (Task 5). A detailed description of the activities carried out in these areas is given in the following report, along with the aims and goals of the work. We will see that we have completed Tasks 2 and 3 fully, and the durability of the resulting device structure has been unaffected. Some of Task 4 was not carried out because of difficulties with integrating the installation of the required targets into the production coater due to external constraints not related to this project. We will also see that the durability of the devices produced as a result of this work was largely unaffected by the changes made here, and so we can conclude that the objectives of Task 5 have also been fulfilled. As a result, the future production of EC windows has benefited greatly from this work. We anticipate higher volumes and better yields for devices with an improved EC performance from the new high volume manufacturing facility currently under construction at SAGE.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Deliverable D11 – Data Sharing, Storage, Security Protocols, and a Specification of a Potential Data Sharing Portal

Pacific Northwest National Laboratory (PNNL) and Technical University of Denmark (DTU) completed this deliverable as part of Work Package 2: Data Information Catalog for Distributed Wind Research for the International Energy Agency (IEA) Wind Technology Collaboration Programme Task 41: Enabling Wind to Contribute to a Distributed Energy Future. As part of the work plan, Deliverable D11 requires the development of data sharing, storage, and security protocols for metadata to be stored on the platform, if needed. The specification of a potential data sharing portal that expands on the catalog is also required.

17 WIND ENERGY↗

Assessment of the dose reduction potential of a model-based iterative reconstruction algorithm using a task-based performance metrology

Purpose: Different computed tomography (CT) reconstruction techniques offer different image quality attributes of resolution and noise, challenging the ability to compare their dose reduction potential against each other. The purpose of this study was to evaluate and compare the task-based imaging performance of CT systems to enable the assessment of the dose performance of a model-based iterative reconstruction (MBIR) to that of an adaptive statistical iterative reconstruction (ASIR) and a filtered back projection (FBP) technique. Methods: The ACR CT phantom (model 464) was imaged across a wide range of mA setting on a 64-slice CT scanner (GE Discovery CT750 HD, Waukesha, WI). Based on previous work, the resolution was evaluated in terms of a task-based modulation transfer function (MTF) using a circular-edge technique and images from the contrast inserts located in the ACR phantom. Noise performance was assessed in terms of the noise-power spectrum (NPS) measured from the uniform section of the phantom. The task-based MTF and NPS were combined with a task function to yield a task-based estimate of imaging performance, the detectability index (d′). The detectability index was computed as a function of dose for two imaging tasks corresponding to the detection of a relatively small and a relatively large feature (1.5 and 25 mm, respectively). The performance of MBIR in terms of the d′ was compared with that of ASIR and FBP to assess its dose reduction potential. Results: Results indicated that MBIR exhibits a variability spatial resolution with respect to object contrast and noise while significantly reducing image noise. The NPS measurements for MBIR indicated a noise texture with a low-pass quality compared to the typical midpass noise found in FBP-based CT images. At comparable dose, the d′ for MBIR was higher than those of FBP and ASIR by at least 61% and 19% for the small feature and the large feature tasks, respectively. Compared to FBP and ASIR, MBIR indicated a 46%–84% dose reduction potential, depending on task, without compromising the modeled detection performance. Conclusions: The presented methodology based on ACR phantom measurements extends current possibilities for the assessment of CT image quality under the complex resolution and noise characteristics exhibited with statistical and iterative reconstruction algorithms. The findings further suggest that MBIR can potentially make better use of the projections data to reduce CT dose by approximately a factor of 2. Alternatively, if the dose held unchanged, it can improve image quality by different levels for different tasks.

60 APPLIED LIFE SCIENCES↗

Estimating the Contributions to Human Error Probability from the Convolution of the Distribution of Time Available and Time Required

As part of their duties, Human Reliability Analysis must often evaluate if crews in nuclear power plants (NPPs) can complete tasks associated with a human-failure event within time limits. For example, the time required in NPP scenarios is determined by systematic and structured walkthroughs, feasibility studies, recorded times from training exercises, and interviews with experienced operators and experts. Typically, a point estimate is derived for the estimate (mean, maximum, or 95th percentile of time required). Using point-estimate values can mask the risk associated with variability among crews, plant conditions and set-up, environmental conditions, and other impact factors under which these actions are executed. While point estimates for time required and time available have served the industry well, without considering the uncertainty they could lead to biased understanding about the risk. The Integrated Human Event Analysis System - General Methodology (IDHEAS-G) model (developed by the US Nuclear Regulatory Commission, NRC) for human error probability calculates human error probability by summing two probabilities: insufficient time and cognitive error. As such, the model takes a more holistic approach by considering the full distributions for time required and time available to calculate the human error probability because the time available to complete the task is insufficient. In this study, we expand on the work of the NRC and discuss methods for estimating these time considerations. For example, for the time required, the impact of Performance Influencing Factors (PIFs) on the distribution was divided into impacts that are aleatory in nature, such as crew-to-crew variability, and those that are epistemic (i.e., the PIFs). Starting with the factors that introduce aleatory uncertainty, a first-order distribution was developed from a large set of time required (i.e., NPP task completion times) data for the range of operator actions that occur in the NPP control room under simulated accident conditions. The first-order distribution can then be adjusted to account for epistemic uncertainty using research associated with the impact of applicable PIFs on the time required. We also develop guidance for analysts to address the probability distributions for the time available. The guidance we developed on how to estimate time required and time available distributions is based on the identification of pertinent research and data, data analyses, and expert knowledge elicitation.

human error probability, human performance, time e↗

Review of Bison Usage in VERA

Bison is being used in VERA in a variety of ways; this milestone will document an independent review of the current usage of Bison and provide guidance that will improve the accuracy, performance, and consistency in the ways that Bison is used. This task will entail running a suite of small, single and multi-cycle problems with VERA-CS, followed by Bison, and Tiamat (inline) and evaluating the usage. It will also entail performing several detailed ramp to full power solutions to compare the one-way coupled solver with the fully-coupled Tiamat. This will include at least one iteration with the PHI team to incorporate some of the feedback and improve the usage. This work will also be completed in conjunction with an FMC task to evaluate the ability of Bison to model load-follow in a PWR

97 MATHEMATICS AND COMPUTING↗

Automatic Halo Management for the Uintah GPU-Heterogeneous Asynchronous Many-Task Runtime

The Uintah computational framework is used for the parallel solution of partial differential equations on adaptive mesh refinement grids using modern supercomputers. Uintah is structured with an application layer and a separate runtime system. Uintah is based on a distributed directed acyclic graph of computational tasks, with a task scheduler that efficiently schedules and executes these tasks on both CPU cores and on-node accelerators. The runtime system identifies task dependencies, creates a task graph prior to the execution of these tasks, automatically generates MPI message tags, and automatically performs halo transfers for simulation variables. Automating halo transfers in a heterogeneous environment poses significant challenges when tasks compute within a few milliseconds, as runtime overhead affects wall time execution, or when simulation variables require large halos spanning most or all of the computational domain, as task dependencies become expensive to process. These challenges are magnified at production scale when application developers require each compute node perform thousands of different halo transfers among thousands simulation variables. The principal contribution of this work is to (1) identify and address inefficiencies that arise when mapping tasks onto the GPU in the presence of automated halo transfers, (2) implement new schemes to reduce runtime system overhead, (3) minimize application developer involvement with the runtime, and (4) show overhead reduction results from these improvements.

Concurrency↗

Mobile Technology and Social Media in the Clinical Practice of Young Radiation Oncologists: Results of a Comprehensive Nationwide Cross-sectional Study

Purpose: Social media and mobile technology are transforming the way in which young physicians are learning and practicing medicine. The true impact of such technologies has yet to be evaluated. Methods and Materials: We performed a nationwide cross-sectional survey to better assess how young radiation oncologists used these technologies. An online survey was sent out between April 24, 2013, and June 1, 2013. All residents attending the 2013 radiation oncology French summer course were invited to complete the survey. Logistic regressions were performed to assess predictors of use of these tools in the hospital on various clinical endpoints. Results: In all, 131 of 140 (93.6%) French young radiation oncologists answered the survey. Of these individuals, 93% owned a smartphone and 32.8% owned a tablet. The majority (78.6%) of the residents owning a smartphone used it to work in their department. A total of 33.5% had more than 5 medical applications installed. Only 60.3% of the residents verified the validity of the apps that they used. In all, 82.9% of the residents had a social network account. Conclusions: Most of the residents in radiation oncology use their smartphone to work in their department for a wide variety of tasks. However, the residents do not consistently check the validity of the apps that they use. Residents also use social networks, with only a limited impact on their relationship with their patients. Overall, this study highlights the irruption and the risks of new technologies in the clinical practice and raises the question of a possible regulation of their use in the hospital.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Interpreting Tafel behavior of consecutive electrochemical reactions through combined thermodynamic and steady state microkinetic approaches

Assessing the reaction pathway of multi-electron-transfer reactions is an essential yet difficult task for the rational design of electrocatalysts. In this work, we develop a heuristic approach that combines thermodynamic adsorption energetics calculated through density functional theory with microkinetic modeling using the steady state approximation to interpret the potential-dependent Tafel behavior of consecutive electrochemical reactions. In doing so, we introduce a kinetic framework for ab initio calculations that ensures self-consistent adsorption energetics based on kinetically limited adsorbate coverages. The approach is applied to experimental results on CoO x (OH) 2-x single crystal electrocatalyst particles yielding coverage dependent mechanistic information and identification of the rate-limiting step with standard rate constants for the oxygen evolution reaction on the ($11\bar{2}0$) surfaces of the β-Co(OH) 2 , β-CoOOH, and CoO 2 bulk phases. Finally, this generalizable method enables catalyst benchmarking based on determining the active species involved and associated intrinsic reaction rate constants in consecutive multi-electron-transfer reactions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

The WorkQueue project: A task queue for the CMS workload management system

We present the development and first experience of a new component (termed WorkQueue) in the CMS workload management system. This component provides a link between a global request system (Request Manager) and agents (WMAgents) which process requests at compute and storage resources (known as sites). These requests typically consist of creation or processing of a data sample (possibly terabytes in size). Unlike the standard concept of a task queue, the WorkQueue does not contain fully resolved work units (known typically as jobs in HEP). This would require the WorkQueue to run computationally heavy algorithms that are better suited to run in the WMAgents. Instead the request specifies an algorithm that the WorkQueue uses to split the request into reasonable size chunks (known as elements). An advantage of performing lazy evaluation of an element is that expanding datasets can be accommodated by having job details resolved as late as possible. The WorkQueue architecture consists of a global WorkQueue which obtains requests from the request system, expands them and forms an element ordering based on the request priority. Each WMAgent contains a local WorkQueue which buffers work close to the agent, this overcomes temporary unavailability of the global WorkQueue and reduces latency for an agent to begin processing. Elements are pulled from the global WorkQueue to the local WorkQueue and into the WMAgent based on the estimate of the amount of work within the element and the resources available to the agent. WorkQueue is based on CouchDB, a document oriented NoSQL database. The WorkQueue uses the features of CouchDB (map/reduce views and bi-directional replication between distributed instances) to provide a scalable distributed system for managing large queues of work. The project described here represents an improvement over the old approach to workload management in CMS which involved individual operators feeding requests into agents. This new approach allows for a system where individual WMAgents are transient and can be added or removed from the system as needed.

Ryu, S.↗

MATEY: multiscale adaptive transformer models for spatiotemporal physical systems

Accurate representation of the multiscale features in spatiotemporal physical systems using vision transformer architectures requires extremely long, computationally prohibitive token sequences. To address this issue, we propose two novel adaptive tokenization schemes that dynamically adjust patch sizes based on local features: one ensures convergent behavior to uniform patch refinement, while the other offers better computational efficiency. Moreover, we present a set of spatiotemporal attention schemes, where the temporal or axial spatial dimensions are decoupled, to evaluate their baseline computational and data efficiencies and to determine whether adaptive tokenization can improve this performance. We assess the performance of the proposed multiscale adaptive model, MATEY, in a sequence of experiments. Compared to a full spatiotemporal attention scheme or a scheme that decouples only the temporal dimension, we find that fully decoupled axial attention is less efficient and expressive, requiring more training time and model parameters to achieve the same accuracy. The experiments on the adaptive tokenization schemes show that, compared to a uniformly refined model, the proposed schemes achieve comparable or improved accuracy at a much lower cost in the tested two-dimensional settings. While the asymptotic analysis suggests the potential for favorable scaling, empirical validation at substantially longer sequence lengths remains to be performed in future work. Finally, we demonstrate in two fine-tuning tasks featuring different physics that models pretrained on PDEBench data outperform the ones trained from scratch, especially in the low data regime with frozen attention.

adaptive tokenization↗