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This is a summary of the work of Group 3 of the International PV QA Task Force. Group 3 is chartered to develop accelerated stress tests that can be used as comparative predictors of module lifetime versus stresses associated with humidity, temperature and voltage.
Distributed acoustic sensors (DAS) have shown remarkable success in monitoring critical civil, energy and transportation assets over long distances and under harsh environmental conditions. Integration of artificial intelligence (AI) technologies with DAS can extend their operational capabilities from conventional tasks (e.g., vibration frequency detection) to more advanced intelligent tasks like anomaly detection. However, these AI technologies often require large labeled/ annotated DAS measurements datasets of the assets in both normal and anomalous operating conditions. This data acquisition task can be both time consuming and costly. This work develops a generative adversarial network based unsupervised domain adaptation framework to build intelligent DAS operational capabilities.
The OECD Nuclear Energy Agency (NEA) Task Group on Radiological Characterisation and Decommissioning within the Working Party on Decommissioning and Dismantling (WPDD) was established in 2011 to identify and present characterisation good practice at different stages of decommissioning and to identify areas that could, or should, be developed further through international cooperation and coordination. By the mid 2017 two phases of work will be complete. The first phase developed strategic guidance for decision makers on the selection and tailoring of strategies for radiological characterisation, which gives an overview of good practice for radiological characterisation at different phases of the life cycle of a nuclear installation. The second phase has focused on strategies for practical implementation of radiological characterisation from a waste and materials end-state perspective. This paper provides a summary of the phase 2 findings. (authors)
The present work is a continuation of the 2020 IEA PVPS Task 12 Human Health Risk Assessment Methods for PV Part 3: Module Disposal Risks. The 2020 report performed a human health risk assessment (HHRA) for disposal of a cadmium telluride (CdTe) PV module in an unlined landfill, focusing solely on risks from cadmium. This study extends the 2020 HHRA on CdTe PV, analyzing eleven constituent elements: Cd, Se, Te, Cu, Si, Cr(III), Mo, Sn, Zn, Ni, and Al. The present HHRA was performed through two methods: utilization of the U.S. Environmental Protection Agency's (USEPA) Delisting Risk Assessment Software (DRAS V.4.0) on eight exposure pathways for cancer risk and non-cancer hazards; and comparison of exposure point concentrations to federal standards for groundwater, surface water, air, and soil exposure pathways. Cancer risks and non-cancer hazards posed by elemental leaching through all evaluated exposure pathways, using both methods, were found to be several orders of magnitude below USEPA health-protective thresholds. Cadmium exhibited both the highest risks and lowest uncertainty considering data availability on chemical content, leachate, and federal screening levels.
FPGA-based SmartNICs offer great potential to significantly improve the performance of high-performance computing and warehouse data processing by tightly coupling support for reconfigurable data-intensive computation with cross-node communication, thereby mitigating the von Neumann bottleneck. Existing work, however, has been generally been limited in that it assumes an accelerator model where kernels are offloaded to SmartNICs, but most control tasks are left to the CPUs. This leads to frequent waiting, inferior performance, and scaling challenges. In this work, we propose a new distributive data-centric computing framework, named FCsN, for reconfigurable SmartNIC-based systems. Through a lightweight task circulation execution model and its implementation architecture, FCsN allows the complete detaching of kernel execution, control logic, system scheduling, and network communication to the SmarNICs. This boosts performance by: (i) avoiding the control dependency with CPUs and (ii) supporting streaming kernel execution and network communication at line rate and in a very fine-grained manner. We demonstrate the efficiency and flexibility of FCsN using various types of neural network applications including graph neural networks; as these last are both irregular and data intensive they offer an especially robust demonstration. Evaluations using commonly-used neural network models and graph datasets show that a system with the support of FCsN can achieve, on average, 144 speedups over the MPI-based standard CPU baselines.
The bulk transfer coefficients of momentum, heat, and humidity belong to the main ingredients of numerical weather prediction and climate models. They are needed for the calculation of turbulent fluxes in the surface layer and often rely on the Monin–Obukhov similarity theory requiring universal stability functions. The problem of a derivation of transfer coefficients based on different stability functions has been considered by many researchers over the years but it remains to this day. In this work, dedicated to the memory of S.S. Zilitinkevich, we also address this task, and obtain transfer coefficients from three pairs of theoretically derived stability functions suggested by Zilitinkevich and co-authors for stable conditions. Additionally, we construct non-iterative parametrizations of these transfer coefficients based on earlier work. Results are compared with state-of-the-art coefficients for land, ocean, and sea ice. The combined parametrizations form a package in a universal framework relying on a semi-analytical solution of the Monin-Obukhov similarity theory equations. A comparison with data of the Surface Heat Budget of the Arctic Ocean campaign (SHEBA) over sea ice reveals large differences between the coefficients for land conditions and the measurements over sea ice. However, two schemes of Zilitinkevich and co-authors show, after slight modification, good agreement with SHEBA although they had not been especially developed for sea ice. One pair of the modified transfer coefficients is superior and is compatible to earlier SHEBA-based parametrizations. Finally, an algorithm for practical use of all transfer coefficients in climate models is given.
Sandia National Laboratories (SNL) continued evaluation of total system performance assessment (TSPA) computing systems for the previously considered Yucca Mountain Project (YMP). This was done to maintain the operational readiness of the computing infrastructure (computer hardware and software) and knowledge capability for total system performance assessment (TSPA) type analysis, as directed by the National Nuclear Security Administration (NNSA), DOE 2010. This work is a continuation of the ongoing readiness evaluation reported in Lee and Hadgu (2014), Hadgu et al. (2015) and Hadgu and Appel (2016). The TSPA computing hardware (CL2014) and storage system described in Hadgu et al. (2015) were used for the current analysis. One floating license of GoldSim with Versions 9.60.300, 10.5, 11.1 and 12.0 was installed on the cluster head node, and its distributed processing capability was mapped on the cluster processors. Other supporting software were tested and installed to support the TSPA- type analysis on the server cluster. The current tasks included preliminary upgrade of the TSPA-LA from Version 9.60.300 to the latest version 12.0 and address DLL-related issues observed in the FY16 work. The model upgrade task successfully converted the Nominal Modeling case to GoldSim Versions 11.1/12. Conversions of the rest of the TSPA models were also attempted but program and operational difficulties precluded this. Upgrade of the remaining of the modeling cases and distributed processing tasks is expected to continue. The 2014 server cluster and supporting software systems are fully operational to support TSPA-LA type analysis.
Test plan for FY20 work on ASNF work. Current Status and Proposed Test Matrix: Corrosion testing has been delayed due to iron contamination of corroded samples – investigations as to the source of this is underway and plans for mitigation for the next round in place. Completed pristine Al1100 coupon irradiations under argon and nitrogen atmospheres of various relative humidities were undertaken and reported in December 2019. This work contributed to Milestone 2.6 and Milestone 2.8. The agreed total absorbed doses for this work were 250, 500, 750, and 1000 kGy. However, the new proposed work to be undertaken at SRNL includes total doses of 50 and 100 kGy. Additional total gamma doses will also include pre-corroded samples, so thorough comparisons can be made. Samples in helium head spaces will be prioritized.
We present a deep learning approach for vertex reconstruction of neutrino-nucleus interaction events, a problem in the domain of high energy physics. In this approach, we combine both energy and timing data that are collected in the MIN-ERvA detector to perform classification and regression tasks. We show that the resulting network achieves higher accuracy than previous results while requiring a smaller model size and less training time. In particular, the proposed model outperforms the state-of-the-art by 4.00% on classification accuracy. For the regression task, our model achieves 0.9919 on the coefficient of determination, higher than the previous work (0.96).
Numerical simulations become a necessity when experimental approaches cannot cover the required physical and time scale of interest. One of such area is a simulation of long-term host rock behaviors for nuclear waste disposal and simulation tools involved in the assessment must go through rigorous validation tests. The DECOVALEX project (Development of COupled models and their VAlidation against EXperiments) is dedicated to this purpose by international participants. This work is part of the ongoing phase DECOVALEX–2023 (D–2023, Task G) particularly aiming to simulate fracture behaviors under various conditions. Here, in this study, we cross-verified a variety of numerical methods including continuous and discontinuous approaches against four benchmark exercises with emphasis on numerical accuracy and parameterization of the various numerical approaches. The systematic inter-comparisons of test cases highlight advantages and disadvantages of the different numerical models. Numerical details on discretization effects (e.g. mesh density and orientation) and domain size were investigated in detail for practical applications. It became evident that meticulous attention to mesh resolution and domain size is imperative for achieving accurate numerical simulations, even for static cracks. Moreover, when comparing numerical methods to closed-form solutions for static cracks, all models successfully reproduced the maximum crack opening but encountered challenges near the crack tips. Finally, the paper discusses how to convert between and therefore compare parameters of various numerical approaches. Our benchmark studies reveal that each model necessitates a distinct number of parameters, even in simple scenarios like static crack aperture benchmarks. It is generally more practical to employ fewer parameters to mitigate model over-parameterization and enhance experimental feasibility.
Objectives This study examined predictors of lung cancer mortality, beyond age and smoking, among construction workers employed at US Department of Energy (DOE) sites to better define eligibility for low-dose CT (LDCT) lung cancer screening. Methods Predictive models were based on 17 069 workers and 352 lung cancer deaths. Risk factors included age, gender, race/ethnicity, cigarette smoking, years of trade or DOE work, body mass index (BMI), chest X-ray results, spirometry results, respiratory symptoms, beryllium sensitisation and personal history of cancer. Competing risk Cox models were used to obtain HRs and to predict 5-year risks. Results Factors beyond age and smoking included in the final predictive model were chest X-ray changes, abnormal lung function, chronic obstructive pulmonary disease (COPD), respiratory symptoms, BMI, personal history of cancer and having worked 5 or more years at a DOE site or in construction. Risk-based LDCT eligibility demonstrated improved sensitivity, specificity and positive predictive value compared with current US Preventive Services Task Force guidelines. The risk of lung cancer death from 5 years of work in the construction industry or at a DOE site was comparable with the risk from a personal cancer history, a family history of cancer or a diagnosis of COPD. LDCT eligibility criteria used for DOE construction workers, which includes factors beyond age and smoking, identified 86% of participants who eventually would die from lung cancer compared with 51% based on age and smoking alone. Conclusions Results support inclusion of risk from occupational exposures and non-malignant respiratory clinical findings in LDCT clinical guidelines.
This progress report describes work performed during FY20 at Sandia National Laboratories (SNL) to assess the localized corrosion performance of container/cask materials used in the interim storage of spent nuclear fuel (SNF). Of particular concern is stress corrosion cracking (SCC), by which a through-wall crack could potentially form in a canister outer wall over time intervals that are shorter than possible dry storage times. Work in FY20 further defined our understanding of the potential chemical and physical environment present on canister surfaces, evaluated the relationship between the environment and the resultant corrosion that occurs, and initiated crack growth rate testing under relevant environmental conditions. In FY20, work to define dry storage canister surface environments included several tasks. First, collection of dust deposition specimens from independent spent fuel storage installation (ISFSI) site locations helped to establish a more complete understanding of the potential chemical environment formed on the canister. Second, the predicted evolution of canister surface relative humidity RH) values was estimated using ISFSI site weather data and the horizontal canister thermal model used by the SNL probabilistic SCC model. These calculations determined that for typical ISFSI weather conditions, seasalt deliquescence to produce MgCl2-rich brines could occur in less than 20 years at the coolest locations on the canister surface, and, even after nearly 300 years, conditions for NaCl deliquescence (75% RH) are not reached. This work illustrates the importance of understanding the stability of MgCl2-rich brines on the heated canister surface, and the potential impact of brine composition on corrosion processes, including pitting and stress corrosion cracking. In an additional study, the description of the canister surface environment was refined in order to define more realistic corrosion testing environments including diurnal cycles, soluble salt chemistries, and inert mineral particles. The potential impacts of these phenomena on canister corrosion are being evaluated experimentally. Finally, work over the past few years to evaluate the stability of magnesium chloride brines continued in FY20. MgCl2 degassing experiments were carried out, confirming that MgCl2 brines slowly degas HCl on heated surfaces, converting to less deliquescent magnesium hydroxychloride phases and potentially leading to brine dryout.
The MPACT code provides the capability to calculate the steady-state and transient reactor core neutron distribution for operating nuclear power plant (PWR) conditions across multiple fuel cycles. As required in the CASL SQA plan, it is the responsibility of UM and ORNL as joint owners of MPACT to ensure that verification and validation activities are performed and documented in a V&V manual with supporting publications and CASL technical reports which can be distributed for reference and distribution within VERA. This document provides the first revision of the MPACT verification and validation (V&V) manual and describes the current state of MPACT V&V and updates the framework for future MPACT V&V activities. During FY16, MPACT V&V activities in the areas of code verification have continued to mature and work has progressed on code error evaluation using the Method of Manufactured Solutions (MMS). Several specific tasks have also been completed to improve MPACT code verification to include tasks to improve the unit and regression test coverage. A joint UM/ORNL task was completed to develop standardize coding standards and workflow for the continued collaborative development of MPACT. During the past year, MPACT validation work has continued in both the areas of measured data from critical experiments as well as measured data from operating nuclear power plants. Preliminary work was also performed in FY16 on the use of post-irradiation examinations for evaluation and validation of the isotopic depletion capability in MPACT. Based on the results of V&V efforts this past year, the confidence level has increased in the ability of MPACT to model an operational Pressurized Water Reactor. Areas were identified which require increased emphasis during FY17 to include updating all the V&V problems with the new 51-group library, the completion of cycle 2 of the BEAVRS benchmark, initial validation for BWR applications, the addition of Uncertainty Quantification results into the benchmark results, and the completion of specific validation tasks for the CASL Challenge problems.
Many distributed applications implement complex data flows and need a flexible mechanism for routing data between producers and consumers. Recent advances in programmable network interface cards, or SmartNICs, represent an opportunity to offload data-flow tasks into the network fabric, thereby freeing the hosts to perform other work. System architects in this space face multiple questions about the best way to leverage SmartNICs as processing elements in data flows. In this paper, we advocate the use of Apache Arrow as a foundation for implementing data-flow tasks on SmartNICs. We report on our experiences adapting a partitioning algorithm for particle data to Apache Arrow and measure the on-card processing performance for the BlueField-2 SmartNIC. Our experiments confirm that the BlueField-2’s (de)compression hardware can have a significant impact on in-transit workflows where data must be unpacked, processed, and repacked.
Background: We propose a method for automatic extraction of protein-specific residue mentions from the biomedical literature. The method searches text for mentions of amino acids at specific sequence positions and attempts to correctly associate each mention with a protein also named in the text. The methods presented in this work will enable improved protein functional site extraction from articles, ultimately supporting protein function prediction. Our method made use of linguistic patterns for identifying the amino acid residue mentions in text. Further, we applied an automated graph-based method to learn syntactic patterns corresponding to protein-residue pairs mentioned in the text. We finally present an approach to automated construction of relevant training and test data using the distant supervision model. Results: The performance of the method was assessed by extracting protein-residue relations from a new automatically generated test set of sentences containing high confidence examples found using distant supervision. It achieved a F-measure of 0.84 on automatically created silver corpus and 0.79 on a manually annotated gold data set for this task, outperforming previous methods. Conclusions: The primary contributions of this work are to (1) demonstrate the effectiveness of distant supervision for automatic creation of training data for protein-residue relation extraction, substantially reducing the effort and time involved in manual annotation of a data set and (2) show that the graph-based relation extraction approach we used generalizes well to the problem of protein-residue association extraction. This work paves the way towards effective extraction of protein functional residues from the literature.
The objective of the proposed work was to demonstrate the feasibility of a step change in power plant efficiency at a commercially viable cost, by obtaining performance data for prototype, compact, ceramic microchannel heat exchangers. By performing the tasks described in the initial proposal, all of the milestones were met. The work performed will advance the technology from Technology Readiness Level 3 (TRL 3) to Technology Readiness Level 4 (TRL 4) and validate the potential of using these heat exchangers for enabling high efficiency solid oxide fuel cell (SOFC) or high-temperature turbine-based power plants. The attached report will describe how this objective was met. In collaboration with The Colorado School of Mines (CSM), specifications were developed for a high temperature heat exchanger for three commercial microturbines. Microturbines were selected because they are a more mature commercial technology than SOFC, they are a low-volume and high-value target for market entry of high-temperature heat exchangers, and they are essentially scaled-down versions of turbines used in utility-scale power plants. Using these specifications, microchannel dimensions were selected to meet the performance requirements. Ceramic plates were fabricated with microchannels of these dimensions. The plates were tested at room temperature and elevated temperature. Plates were joined together to make modular, heat exchanger stacks that were tested at a variety of temperatures and flow rates. Although gas flow rates equivalent to those in microturbines could not be achieved in the laboratory environment, the results showed expected efficiencies, robust operation under significant temperature gradients at high temperature, and the ability to cycle the stacks. Details of the methods and results are presented in this final report.
One of the most daunting tasks for any new member of a local board of the Environmental Management Site Specific Advisory Board (EM SSAB) is to try to understand the scope of the clean-up activities going on at the site. In most cases, there are at least two or three major cleanup activities in progress as well as monitoring of past projects. When planning for future projects is added to the mix, the list of projects can be long. With the clean-up activities involving all major environmental media - air, water, soils, and groundwater, new EM SSAB members can find themselves totally overwhelmed and ineffective. Helping new members get over this initial hurdle is a major objective of EM and all local boards of the EM SSAB. Even as members start to understand the size and scope of the projects at a site, they can still be frustrated at the length of time it takes to see results and get projects completed. Many project and clean-up timelines for most of the sites go beyond 10 years, so it's not unusual for an EM SSAB member to see the completion of only 1 or 2 projects over the course of their 6-year term on the board. This paper explores the annual work planning process of the EM SSAB local boards, one tool that can be used to educate EM SSAB members into seeing the broader picture for the site. EM SSAB local work plans divide the site into projects focused on a specific environmental issue or media such as groundwater and/or waste disposal options. Projects are further broken down into smaller segments by highlighting major milestones. Using these metrics, local boards of the EM SSAB can start to quantify the effectiveness of the project in achieving the ultimate goal of site clean-up. These metrics can also trigger board advice and recommendations for EM. At the beginning of each fiscal year, the EM SSAB work plan provides a road map with quantifiable checkpoints for activities throughout the year. When the work plans are integrated with site-specific, enforceable regulatory milestones, they can provide a comprehensive work plan for not only the board, but also regulators, site contractors, and DOE. Because the work plans are reviewed and approved by DOE, they carry some weight in holding local boards of the EM SSAB accountable. This structure provides the basis for local boards to achieve their primary function, to provide DOE with information, advice, and recommendations concerning issues affecting the EM program at the site. (authors)
This thesis covers work performed for the Accelerator Neutrino Neutron Interaction Experiment (ANNIE) between 2015 and 2020. ANNIE is a beamline neutrino experiment located at the Fermi National Accelerator Laboratory in Chicago. Its primary physics goals are the measurement of neutrino interaction cross-sections on oxygen, and a measurement of the multiplicity of final state neutrons from these interactions, both as functions of final state kinematics. In order to achieve these goals ANNIE will be pioneering the use of Large Area Picosecond Photodetectors and the use of gadolinium doping to enhance neutron visibility in a water Cherenkov detector. Over the time period of this thesis the ANNIE detector was constructed, an initial 'Phase I' background run was completed, the detector was decommissioned and then substantially upgraded in preparation for the main 'Phase II' physics run. At the time of writing ANNIE is being re-commissioned, with Phase II data taking anticipated to begin in 2021. During this time I spent 21/2 years on-site contributing to almost all aspects of hardware work, while performing software development for the simulation and analysis frameworks. As my first software task I developed Monte Carlo simulations of the detector response, based on the WCSim framework. While thismore » framework provided a starting point for the tank simulation significant modifications were required to implement the complete ANNIE detector system. This included a rewrite of the geometry, along with modifications to the photosensor definitions, hit collections, digitization, triggering, input and output interfaces, etc. To take advantage of improved modelling of neutrons in Geant4.10 the physics lists were also reimplemented in the new version format. As part of this work I determined performance metrics based on the output files, calculating kinematic acceptance, detector efficiency and expected event rates. My contributions on reconstruction focused primarily on the MRD, for which I implemented two track reconstruction algorithms, specialised for high and low energy muons. The high energy algorithm achieves >90% efficiency for tracks with at least 8 hits, and is robust against dead paddles and unrelated hits. The low energy algorithm performs a search in combination with tank information to provide sensitivity down to a single MRD hit. Early data handling work for the Phase I background run included writing the code for handling TDC hits and performing studies on neutron detection without the requirement of multi-hit coincidence. As the collaboration moved to a new framework for the Phase II analysis I performed a substantial amount of work to develop the codebase, implementing tools to perform tasks such as file IO, data parsing, waveform processing, event building, timestamp alignment, time clustering, hit residual calculation, event visualisation etc. I helped develop the python API for integrating multi-language tools, and ported the framework into a Singularity container to provide a self-contained environment that…« less