Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Task Performance and Analysis”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,009 records · Page 56
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Accelerating Multivariate Functional Approximation Computation with Domain Decomposition Techniques⋆

Modeling large datasets through Multivariate Functional Approximations (MFA) provide an elegant way to handle many visualization and scientific analysis workflows. The process necessitates scalable data partitioning methods to compute MFA representations efficiently without compromising the accuracy or continuity of the reconstructed solution. We propose a domain -decomposed method for computing the MFA with B -spline bases, which reduces the total work per task and uses a restricted Additive Schwarz (RAS) method to converge the control point data degrees -of -freedom along subdomain boundaries. We provide an in-depth analysis of the parallel approach with domain decomposition solvers, aiming to minimize local subdomain error residuals and recover high -order continuity at subdomain interfaces with appropriate choices of knot overlaps. The communication cost, determined by the overlap regions in the RAS implementation, is optimized to recover the numerical error profile of the single subdomain case. Our proposed method stands in contrast to previous methods, which typically only recover either C 0 or at best C 1 continuity for arbitrary B -spline degree expansions, or those that require post -processing to blend discontinuities in the reconstructed data. We demonstrate the effectiveness of our approach using analytical and real -world datasets in 1D, 2D, and 3D through both strong and weak scaling studies. The performance results indicate that the overall cost of computing the approximation is directly proportional to the underlying nearest -neighbor communication implementation, and is only weakly dependent on the overlap region size that determines the size of the messages. This finding underscores the efficiency and scalability of our proposed method, making it a promising solution for handling large datasets in scientific workflows.

additive Schwarz solvers↗
DOE OSTI2017

NXIS - Well integrity inspection in unconventional gas wells

The objective of this project is to advance the state-of-the-art and to develop an integrity inspection system capable of detecting physical flaws in the wellbore structure of conventional and unconventional hydrocarbon producing wells. Measuring the integrity of multiple wellbore casings and cement annuli for onshore and offshore wells remains a challenging task. We propose a multi-modality inspection system composed of neutron and X(gamma)-ray imaging modalities (nXis) to address the above challenge. The functional principle of this wellbore integrity inspection system is the combination of high-energy modalities, such as X(gamma)-ray and neutron backscatter imaging, with conventional low-energy modalities, such as electromagnetic or ultrasound imaging techniques. By combining multiple sensing modalities into one sensing system and by fusing data between modalities, one can gather more information about the integrity of the wellbore structure compared to simply using multiple sensors individually. Imaging prototypes for gamma, neutron, and electromagnetics were designed, manufactured, and tested at GE Global Research and Starfire Industries. Wellbore phantoms with engineered defects were manufactured and the performance of the developed wellbore integrity inspection tool prototypes was evaluated in a test pit test at an industrial GE Oil & Gas facility. Data analysis and fusion between various inspection techniques show enhanced defect detectability. These exciting results were presented at various technical conferences and discussed with operators in the oil & gas industry. Great interest from oil operators lead to discussions about joint industrial partnerships to move the developed technology from the prototype phase to the product phase.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2019

Update on Investigations of Viability of Cold Spray and FSW as a Spent Nuclear Fuel Dry Storage Canister Mitigation Tool

The purpose of this work is to investigate the use of cold spray and friction stir welding or processing (FSW/P) for repair and mitigation of chloride-induced stress corrosion cracking (CISCC) in dry cask storage system (DCSS) canisters to ensure integrity far beyond their original license period. This report provides a viability analysis of cold spray and friction stir welding for repair and fabrication of DCSS canisters. This report presents experimental work and a research strategy to optimize and evaluate cold spray and FSW/P for CISCC resistance. The literature reports that the following three conditions must exist for CISCC to occur: tensile stress, corrosive environment, and susceptible material. These conditions must be understood and accounted for while evaluating CISCC susceptibility. Furthermore, non-obvious factors, such as surface conditions and geometric confinement, can dramatically increase the intensity of one or more of the three listed conditions for CISCC. Arc welding should be considered for either temporary or permanent repair when combined with a mitigation technology. It is known that alloys used in the existing inventory of spent nuclear fuel storage canisters become sensitized in areas around fusion welds. Technologies, such as cold spray or FSW, can mitigate the sensitization caused by fusion welds. FSW/P and cold spray, potential alternatives for fabrication and repair, are solid-phase processes. No melting occurs and the energy input can be controlled such that no harm is done to the base metal during these processes. FSW/P should be considered for use in new fabrication of canisters and repair of existing canisters. Low heat input and grain refinement result in material with improved mechanical properties and comparable generalized corrosion performance relative to base metal. FSW/P offers the potential of through-thickness CISCC resistance. Cold spray should be considered for production, mitigation, and repair of canisters. Cold spray has demonstrated the ability to deposit stainless steel, Inconel alloys, and other alloys on stainless steel 304L such that galvanic potential is matched and resistance to pitting is improved. The technical basis for cold spray mitigation and repair within the overpack using remote robotic equipment is established. A non-obvious application to the research community is the sealing of crevices. All reported instances of CISCC in the fielded nuclear applications were associated with crevice corrosion. This can be avoided by cold spraying to seal crevices. The bulk of the work planned for FY 2020 will be generating coupons for CISCC testing by collaborative projects at Pacific Northwest National Laboratory and Sandia National Laboratories. First an exploratory study will be executed that will include screening studies and process optimization. This task will identify the effect of process parameters on microstructure and CISCC resistance. Optimized parameters will be used to produce a smaller number of coupons for full testing and evaluation. Test methods for evaluating CISCC resistance must meet the following criteria: (1) normalized surface geometry and exposed process microstructure, (2) account for residual stresses, (3) be in a controlled and appropriate test environment, and (4) be numerically quantifiable and repeatable. Failure to meet these criteria could lead to results that cannot be used for comparative analysis of processes and materials.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2018

Final Report: Scale-up of Algal Biofuel Production Using Waste Nutrients

Renewable fuels can be more environmentally friendly than conventional fuels and can be produced locally, supporting energy independence. Liquid renewable fuels are of special interest due to their high energy density. Algae are a promising prospective feedstock for low carbon intensity liquid biofuels, due to their high productivity and potential for high lipid or carbohydrate content. Their ability to grow on wastewater and waste nutrients and on non-arable land are cost and sustainability advantages. The organic matter content of wastewater promotes mixotrophic and/or heterotrophic growth of both algae and bacteria, boosting biomass productivity further. However, economic and technologic challenges persist that prevent the scale-up of algal biofuels to commercial relevance. These challenges include algal harvesting, drying, dewatering, and the conversion of algal biomass to usable fuels (Hannon et al 2010, Dunlap and Shaw 2009, Pienkos et al. 2009). The US Department of Energy (DOE) Bioenergy Technologies Office (BETO) supports research to overcome these challenges and outlines the research and development goals for algal biofuels in their Multi-Year Program Plan (MYPP). The long-term goals of the MYPP for algal biofuels research are briefly as follows: develop the domestic ability to produce algal biofuels at a scale of 5 billion gallons per year (BGY) by 2030 and demonstrate technologies that produce biofuel intermediates from algae at a cost of $3/gallon of gasoline equivalent (GGE) by 2022 (BETO MYPP 2016). This research reported herein was funded to investigate methods of meeting an intermediate milestone of 2,500 gallons of biofuel intermediate per acre per year for a non-integrated process by improving algal productivity, harvesting efficiency, and conversion to biofuel intermediates. Use of wastewater and wastewater nutrients was a key distinguishing characteristic of this project. In pursuit of 2,500 gallons of biofuel intermediate (BFI) per acre per year, California Polytechnic State University, San Luis Obispo (Cal Poly) sought to develop the capability to produce biofuel intermediates from microalgae grown on municipal wastewater at a 20-acre algae-based wastewater treatment facility in Delhi, California (37.43° N), which includes 7 acres of raceway ponds. Coupling algal biofuel production with wastewater treatment capitalizes on the abundant waste nutrients and carbon present in wastewater and reduces use of clean water in algal biorefinery systems. In this research, the performance of the full-scale wastewater treatment plant was characterized by measuring productivity, wastewater treatment performance, hydraulic characteristics, and energy consumption. Nine 1,000-L pilot raceways with CO2 addition were used in experiments to maximize productivity. Low-cost, energy-efficient algae bioflocculation and settling were monitored. Population genetics were monitored in an attempt to correlate taxa with superior productivity and/or settling. Algae-bacterial biomass was converted to biofuel intermediates via bench-scale hydrothermal liquefaction (HTL), and the resulting fuel quality was characterized. To develop rapid strain screening capabilities, a climate simulating photobioreactor (“LEAPS”) was developed and validated against outdoor raceways. A techno-economic analysis (TEA) and a lifecycle assessment (LCA) were performed to model process economics and sustainability. The major outcomes of this research included demonstration of 33 g/m2-day annual average algal-bacterial productivity in pilot raceways, and a biofuel intermediate yield of 0.35 g intermediate/g algae biomass via HTL, for a yield of 4,100 gallons BFI per acre per year, assuming a 90% harvest efficiency and ignoring other minor losses. This exceeded the project goal of 2,500 gallons of BFI per acre per year and nearly met the 2030 program goal, highlighting the promise of integrating wastewater treatment and biofuels production. The biocrude BFI produced by the process is refined to diesel and naphtha fuels. These fuels are normalized to the energy content of gasoline (gallons gasoline equivalent, GGE, for comparison to other fuels). Results from the TEA of the this complete “well-to-wheel” process demonstrated that, at a 400-ha scale, a minimum fuel selling price (MFSP) of $12.55/GGE, which could be decreased 57% to $7.14/GGE when including revenue from coupling the biofuel production with the co-products of wastewater treatment services and low carbon fuel credits from California and Federal programs. Due mainly to the high capital costs of thickener centrifuges and hydrothermal processing equipment, the fuel cost is sensitive to scale, with significantly lower costs expected for larger farms. In this research project, significant advances were made in improving raceway algal productivity and fuel production from algae biomass, while also improving process economics. These outcomes brought the algal biofuel technology closer to being a sustainable and marketable process. The remainder of this executive summary is organized into the following six primary project tasks: (1) to optimize biomass productivity for a selected strain at Delhi, (2) to maximize algal productivity and harvesting efficiency in Delhi pilot ponds, (3) a full-scale raceway hydraulic characterization, (4) biomass processing to biofuel intermediates, and (5) scale-up engineering analysis, modeling, and planning.

09 BIOMASS FUELS↗
DOE OSTI2017

2005 ACGIH Lifting TLV: Employee-Friendly Presentation and Guidance for Professional Judgment

The American Council of Governmental Industrial Hygienists (ACGIH) Lifting Threshold Limit Values (TLVs) provide a tool to reduce incidence of low back and shoulder injuries. However, application of the TLV is too complicated for floor-level workers and relies on professional judgment to assess commonly encountered tasks. This paper presents an Employee-Friendly Simplified Format of the TLV that has been adapted from Table 1 of the Lifting TLV presented in the 2005 TLVs and BEIs Based on the Documentation of the Threshold Limit Values for Chemical Substances and Physical Agents & Biological Exposure Indices. This simplified format can be employed by floor-level workers to self-assess lifting tasks. The Ergonomics Project Team also provides research-based guidance for applying professional judgment consistent with standard industry practice: Extended Work Shifts – Reduce weight by 20% for shifts lasting 8 to 12 hours; Constrained Lower Body Posture – Reduce weight by 25% when lifting in such postures; Infrequently Performed Lifts – Lift up to 15 lbs. ≤3 lifts per hour within the zones marked “No safe limit for repetitive lifting” in the TLVs Table 1; Asymmetry beyond 30° – Reduce weight by 10 lbs. for lifts with up to 60° asymmetry from sagittal plane.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2026

Task Sharing of Proton Incorporation in Vertically Aligned Nanocomposite Triple Conductors: Growth, Structure, and Surface Exchange Kinetics

As protonic ceramic electrolysis cells emerge for efficient H 2 production, there is a need to develop air electrode materials enabling fast, durable steam splitting and proton incorporation. Single-phase triple conductors may fail to satisfy the myriad performance/stability requirements, and their critical charge-carriers (holes, oxygen vacancies, and protons) are in competition, limiting their concentrations. Instead, we propose task-sharing, vertically aligned nanocomposites (VANs), comprising a proton conductor (BaZr 0.9 Y 0.1 O 3-δ ) and a redox-active mixed ionic electronic conductor (Ce 0.9 Pr 0.1 O 2-δ ), that may enable rapid proton surface exchange at the solid–gas interface and transport along the solid–solid heterointerfaces. We grew VANs by pulsed laser deposition and investigated the interplay between their processing conditions, structure, and proton and oxygen surface exchange kinetics. We varied the substrate temperature, laser repetition rate, laser fluence, and processing oxygen pressure. The crystallinity and phases were characterized by grazing-incidence X-ray diffraction, and the strain and structural order as a function of depth were evaluated by angle-dependent synchrotron X-ray pair distribution function analysis. To evaluate the potential for interdiffusion, the formation energies of substitutional defects were simulated with density functional theory. Corresponding structural analysis and elemental mapping were performed by scanning/transmission electron microscopy, energy-dispersive X-ray spectroscopy, and electron energy-loss spectroscopy, indicating distinct nanoscale compositional regions with a hierarchical structure embedded in individual VANs columns and minimal interdiffusion across a bilayer film. Proton and oxygen surface exchange coefficients (k H , k O ) and polarization resistances were evaluated by electrical and optical relaxations and impedance spectroscopy of VAN-incorporated protonic ceramic electrochemical cells, respectively, at 400–500 °C, demonstrating values comparable to some of the best-known triple and mixed conductors.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Soil Water Retention and Hydraulic Conductivity Data and Model at Trail Creek in Taylor River Watershed, Colorado 2024-2025

This data package includes soil water retention and hydraulic conductivity data and model fitting results from measurements of ex-situ soil samples and in-situ soil sensors near Trail Creek. Soil water retention curves (SWRC) characterize soil water content as a function of soil water potential. SWRC depends on soil texture and pore structure and can be used to describe the constraints on biogeochemical processes in terms of soil water availability. In this data package, the sample identification follows the format TR-X-Y, where TR refers to Trail Creek, X is the treatment block identifier, and Y is the location identifier. Specifically, TR-ASCC1 is the control treatment block under the Adaptive Silviculture for Climate Change (ASCC) project, and TR-ASCC2 is the clear-cut treatment block. TR-ASCC-EHSn is associated with ecohydrology sites under the East-Taylor Watershed Community Observatory Sites directory, and TR-ASCC-ERTn (upslope n=1) are ecohydrology sites along the electrical resistivity tomography transects. The sample and location information can be found in metadata.csv, and the data from the soil sensors will be included in a future data version when the observation period becomes sufficiently long for data analysis. Sampling and Measurements Each sample falls into one of the two sampling methods – (1) intact cores or (2) soil sensors – and one of the two measurement methods – (a) laboratory or (b) in-situ. The intact cores were measured using the laboratory methods, which include measurements of soil water potential (HYPROP & WP4C, METER), saturated (KSAT, METER) and unsaturated hydraulic conductivity (HYPROP). The in-situ method uses a pair of co-located soil sensors to measure volumetric water content (TEROS12, METER) and soil water potential (TEROS21, METER), and the hydraulic conductivity was not measured. In comparison, the laboratory methods progress from full saturation to dry conditions, and the in-situ method includes both dry-to-wet and wet-to-dry cycles. The sampling and measurement methods for each sample can be found in metadata.csv, and more information about the measurements is detailed in the Methods section below. Models Retention and hydraulic conductivity data were fitted with four van-Genuchten-type models (specified by “model_name” column in the files): (1) traditional constrained van Genuchten model (“vG_constrained”), (2) traditional unconstrained van Genuchten model (“vG_unconstrained”), (3) PDI-variant of the constrained van Genuchten model (“vG_constrained_PDI”), and (4) PDI-variant of the unconstrained van Genuchten model (“vG_unconstrained_PDI”). The difference between the constrained (1: n) and the unconstrained (2: n, m) van Genuchten models is the number of pore-size distribution parameters in the model equations, giving the unconstrained model more degrees of freedom when fitting the data. Between the traditional and the PDI-variant models, model fitting differs the most at the dry end of the measurements. The traditional models allow infinite suction at the residual water content (water content does not drop below residual water content), and the PDI-variant models enforce a soil water potential value of pF=6.8 (~ -630 MPa) at oven-dryness (water content reaches 0). The inclusion of the van-Genuchten-type models is due to their common application. If other retention models are required, users can access the data in data.csv for further data fitting. More information about the models can be found in the Methods section below. Fitting Tasks The model fitting can be categorized into three levels of tasks (specified by “fitting_task” column in the files). Level 1 (“fit_retention”) only includes retention data fitting (the only level available for the in-situ method). Level 2 (“fit_retention_conductivity”) includes both retention and hydraulic conductivity data fitting, and the saturated hydraulic conductivity (Ks, a parameter of the hydraulic conductivity functions) is fixed by the measurements from KSAT. Level 3 (“fit_retention_conductivity_Ks”) also includes both retention and hydraulic conductivity data fitting, but Ks is a fitted parameter without the constraints from KSAT measurements. Among the same retention models (e.g. vG_constrained models of the same sample), level 1 should produce the best retention data fitting. Level 2 should have the highest misfit of the retention and hydraulic conductivity data, because the retention and hydraulic conductivity functions share common model parameters, and the unsaturated hydraulic conductivity (HYPROP) data fitting is subject to Ks measured independently by KSAT. Level 3 should have mid-level misfits of the retention and hydraulic conductivity data. While level 3 fits the hydraulic conductivity data better than level 2, the fitted Ks value might be unreasonable due to the lack of constraints at the wet end of the measurements. General recommendation when using this data package: (1) Choice of sampling methods: Intact cores might suffer from sample gaps that would lead to overestimation of Ks (sample gaps can be inferred from the “soil_sample_volume” column in metadata.csv when the value is < 249). In-situ method has higher uncertainty in characterizing the wet end of the SWRC because of sensor limitations and the difficulty in reaching full saturation under natural conditions. (2) Choice of fitting tasks: When only retention data is needed, level 1 (“fit_retention”) should be prioritized. When both retention and hydraulic conductivity data are needed, level 2 (“fit_retention_conductivity”) could be prioritized. (3) Choice of models: This could depend on what the downstream models call for. If no specific model is required, model misfit could be used as a ranking criterion. Model misfit values in terms of RMSE can be found in model_parameters.csv. The following files are included in this data package: (1) metadata.csv – This file includes the general information of each sample, including location (description, geocoordinates, elevation), sampling and measurements details (method, depth, time or period, volume, instruments), and soil physical properties (bulk density, saturated hydraulic conductivity, only applicable to physical soil samples). (2) data.csv – This file includes soil water potential, volumetric water content, and unsaturated hydraulic conductivity data of each sample. Column “instrument” specifies the instrument (HYPROP, WP4C, or TEROS) used to perform the measurements. (3) model_fit.csv – This file includes soil water potential, volumetric water content, and unsaturated hydraulic conductivity fitted from the four models and three fitting tasks. Column “model_name” specifies the retention model used, and “fitting_task” specifies the level of data fitting. Missing values indicate that the variable does not apply to that fitting task. (4) model_parameters.csv – This file includes the fitted model parameters, model misfits, and conventional water content thresholds (field capacity and wilting point) from the four models and three fitting tasks. Column “model_name” specifies the retention model used, and “fitting_task” specifies the level of data fitting. Missing values indicate that the parameter does not apply to that model and/or that fitting task. (5) data_Ks.csv – This file includes the saturated hydraulic conductivity measurements from KSAT. (6) /figure/*.png – This folder includes three quick visualizations of the data, retention model fitting results and misfits, and hydraulic conductivity model fitting results, misfits, and parameters. The model fitting results are separated by samples and fitting tasks and colored by models. Zoom-in required. (7) /hyprop/*.bdhx – This folder includes proprietary hyprop files that require the free Labros SoilView-Analysis (METER) to open. Users can explore data fitting using other retention models (i.e. Brooks-Corey, Fredlund-Xing, Kosugi, bimodal models). Be aware that Ks value is pre-entered under “Fitting tab, Conductivity functions parameters” for level 2 fitting. If the value is lost, please refer to metadata.csv under “Ks” column. (8) Six file-level metadata that summarize file, header, column, and variable information of all files. This work was supported by the Watershed Function Science Focus Area at Lawrence Berkeley National Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-05CH11231.

EARTH SCIENCE > LAND SURFACE > SOILS↗
DOE OSTI2014

Implementing controlled-unitary operations over the butterfly network

We introduce a multiparty quantum computation task over a network in a situation where the capacities of both the quantum and classical communication channels of the network are limited and a bottleneck occurs. Using a resource setting introduced by Hayashi [1], we present an efficient protocol for performing controlled-unitary operations between two input nodes and two output nodes over the butterfly network, one of the most fundamental networks exhibiting the bottleneck problem. This result opens the possibility of developing a theory of quantum network coding for multiparty quantum computation, whereas the conventional network coding only treats multiparty quantum communication.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

Design Concepts for an Outage Control Center Information Dashboard

The nuclear industry, and the business world in general, is facing a rapidly increasing amount of data to be dealt with on a daily basis. In the last two decades, the steady improvement of data storage devices and means to create and collect data along the way influenced the manner in which we deal with information. Most data is still stored without filtering and refinement for later use. Many functions at a nuclear power plant generate vast amounts of data, with scheduled and unscheduled outages being a prime example of a source of some of the most complex data sets at the plant. To make matters worse, modern information and communications technology is making it possible to collect and store data faster than our ability to use it for making decisions. However, in most applications, especially outages, raw data has no value in itself; instead, managers, engineers and other specialists want to extract the information contained in it. The complexity and sheer volume of data could lead to information overload, resulting in getting lost in data that may be irrelevant to the task at hand, processed in an inappropriate way, or presented in an ineffective way. To prevent information overload, many data sources are ignored so production opportunities are lost because utilities lack the ability to deal with the enormous data volumes properly. Decision-makers are often confronted with large amounts of disparate, conflicting and dynamic information, which are available from multiple heterogeneous sources. Information and communication technologies alone will not solve this problem. Utilities need effective methods to exploit and use the hidden opportunities and knowledge residing in unexplored data resources. Superior performance before, during and after outages depends upon the right information being available at the right time to the right people. Acquisition of raw data is the easy part; instead, it is the ability to use advanced analytical, data processing and data visualization methods to turn the data into reliable information and comprehensible, actionable information. Techniques like data mining, filtering and analysis only work reliably for well-defined and well-understood problems. The path from data to decision is more complex. The ability to communicate knowledge during outages and emergent issues is crucial. This paper presents an approach to turn the unused data into an opportunity: applying principles from semiotics, human factors and visual analytics to transform the traditional way of processing outage data into media that will improve the collective situation awareness, knowledge, decisions, actions and overall performance of the entire outage team, and also support the reliability, quality and overall effectiveness of maintenance work. The application of the proposed visualization methods will become the medium of a semi-automated analytical process where humans and machines cooperate using their respective, distinct capabilities for the most effective results.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2024

Strategy to Develop a Control Scheme for Core Thermal Performance Optimization

This report outlines a three-year research plan for optimizing reactor core thermal performance through use of a Digital Twin (DT) model and a set of neutron detectors to correspondingly adapt the reactor control strategy. It identifies reactor features and achievable neutron measurements that factor into this optimization task. It considers spatial effects that are important and how they can be managed by a real-time algorithm that controls reactivity actuators. The report presents a set of tasks, along with corresponding methods, for accomplishing this objective. The final task in this set is to validate the combined optimization procedure in the Purdue University’s PUR-1 reactor, for which we have an agreement of understanding. Additionally, we describe an alternative approach for overcoming some of the limitations inherent in the above approach, which includes the computational costs of high-fidelity simulations and achievable integration of neutron measurements into the DT. The proposed algorithms lower the technology readiness level (TRL) of the overall approach as some additional analysis and the development of a new neutron detector concept are necessary. In particular, a sensor measuring the gradient of the neutron flux is required, and the prototype is expected to be validated in the PUR-1 reactor. The potential benefits and the opportunity to significantly push forward the state-of-the-art make this approach worthy of further exploration in the upcoming years.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2014

SL12-GADRAS-PD2Ka Annual Report

The GADRAS Development project comprises several elements that are all related to the Detector Response Function (DRF), which is the core of GADRAS. An ongoing activity is implementing continuous improvements in the accuracy and versatility of the DRF. The ability to perform rapid computation of the response of gammaray detectors for 3-D descriptions of source objects and their environments is a good example of a recent utilization of this versatility. The 3-D calculations, which execute several orders of magnitude faster than competing techniques, compute the response as an extension of the DRF so the radiation transport problem is never solved explicitly, thus saving considerable computational time. Maintenance of the Graphic User Interface (GUI) and extension of the GUI to enable construction of the 3-D source models is included in tasking for the GADRAS Development project. Another aspect of this project is application of the isotope identification algorithms for search applications. Specifically, SNL is tasked with development of an isotope-identification based search capability for use with the RSL-developed AVID system, which supports simultaneous operation of numerous radiation search assets. A Publically Available (PA) GADRAS-DRF application, which eliminates sensitive analysis components, will soon be available so that the DRF can be used by researchers at universities and corporations.

47 OTHER INSTRUMENTATION↗
DOE OSTI2016

Low-Cost Gas Heat Pump for Building Space Heating

Gas-fired residential space heating in the U.S is predominantly supplied by furnaces and boilers. These technologies have been approaching their thermodynamic limit over the past 30 years and improvements for high efficiency units have approached a point of diminishing return. Electric heat pumps are growing in popularity but their heating performance at low ambient temperatures is poor. The development of a low-cost gas absorption heat pump would offer a significant improvement to current furnaces and boilers, and in heating dominated climate zones when compared to electric heat pumps. Gas absorption heat pumps (GAHP) exceed the traditional limit of thermal efficiency encountered by typical furnaces and boilers, and maintain high levels of performance at low ambient temperatures. The project team designed and demonstrated two low-cost packaged prototype GAHP space heating systems during the course of this investigation. Led by Stone Mountain Technologies Inc. (SMTI), with support from A.O. Smith, and the Gas Technology Institute (GTI), the cross-functional team completed research and development tasks including cycle modeling, 8× scaling of a compact solution pump, combustion system development, breadboard evaluation, fabrication of two packaged prototype units, third party testing of the first prototype, and the evaluation of cost and energy savings compared to high and minimum efficiency gas options. Over the course of the project and with the fabrication of two Alpha prototypes it was shown that this technology met or exceeded most of the stated project targets. At ambient temperatures of 47, 35, 17 and -13°F the prototypes achieved gas based coefficients of performance of 1.50, 1.44, 1.37, and 1.17, respectively. Both units operated with parasitic loads well below the 750 watt target with the second Alpha prototype operating 75-100 watts below the first Alpha prototype. Modulation of the units at 4:1 was achieved with the project goal of 2:1 modulation, which will allow for improved load matching. In addition, the energy savings analysis showed that a house in Albany, NY, Chicago, IL and Minneapolis, MN would save roughly 32, 28.5 and 36.5 MBtu annually when compared to a 100% efficient boiler, respectively. The gas absorption heat pump achieves this performance by using high grade heat from the combustion of natural gas in combination with low grade heat extracted from the ambient to produce medium grade heat suitable for space and water heating. Expected product features include conventional outdoor installation practices, 4:1 modulation, and reasonable economic payback. These factors position the technology to gain significant market penetration, resulting in a large reduction of energy use and greenhouse gas emissions for residential space heating.

03 NATURAL GAS↗
DOE OSTI2025

Scalable edge clustering of dynamic graphs via weighted line graphs

Timestamped relational datasets consisting of records (or connections) between pairs of entities are ubiquitous in network science. For applications like peer-to-peer communication, email, various social network interactions, and computer network security, it is useful to organize these records into groups based on how and when they are occurring. Weighted line graphs offer a natural way to model how records are related in such datasets but for large real-world graph topologies, building and utilizing the line graph is prohibitively expensive. Here, we present the framework to cluster the edges of a dynamic graph via the associated line graph that contains two major contributions. The first is a method to work with the line graph implicitly and the second is a distributed scale implementation of an agglomerative hierarchical graph clustering algorithm. We outline a novel hierarchical dynamic graph edge clustering approach that efficiently breaks massive relational datasets into small sets of edges containing events at various timescales. This is in stark contrast to traditional graph clustering algorithms that prioritize highly connected (clique-like) community structures. Our approach relies on constructing a sufficient subgraph of a weighted line graph and applying a hierarchical agglomerative clustering. This approach is related to scalable techniques from spatial clustering, nonlinear-dimension reduction, topological data analysis, and draws particular inspiration from HDBSCAN. As an edge clustering, this method yields an overlapping node clustering. Our algorithm is parallelizable and we demonstrate efficient clustering of a billion-scale, real-world dynamic graph into small edge sets that correlate in topology and time. The entire clustering process for a graph with tens of billions of edges takes just a few minutes of run time on 256 nodes of a distributed compute environment. We argue how the output of the edge clustering is useful for a multitude of data visualization and powerful machine learning tasks, both involving the original massive dynamic graph data and metadata associated with the nodes and edges. Finally, we describe how this approach can be extended to dynamic hypergraphs and dynamic graphs/hypergraphs with unstructured data living on vertices and edges.

Data Analysis↗
DOE OSTI2015

Continuous Security and Configuration Monitoring of HPC Clusters

Continuous security and configuration monitoring of information systems has been a time consuming and laborious task for system administrators at the High Performance Computing (HPC) center. Prior to this project, system administrators had to manually check the settings of thousands of nodes, which required a significant number of hours rendering the old process ineffective and inefficient. This paper explains the application of Splunk Enterprise, a software agent, and a reporting tool in the development of a user application interface to track and report on critical system updates and security compliance status of HPC Clusters. In conjunction with other configuration management systems, the reporting tool is to provide continuous situational awareness to system administrators of the compliance state of information systems. Our approach consisted of the development, testing, and deployment of an agent to collect any arbitrary information across a massively distributed computing center, and organize that information into a human-readable format. Using Splunk Enterprise, this raw data was then gathered into a central repository and indexed for search, analysis, and correlation. Following acquisition and accumulation, the reporting tool generated and presented actionable information by filtering the data according to command line parameters passed at run time. Preliminary data showed results for over six thousand nodes. Further research and expansion of this tool could lead to the development of a series of agents to gather and report critical system parameters. However, in order to make use of the flexibility and resourcefulness of the reporting tool the agent must conform to specifications set forth in this paper. This project has simplified the way system administrators gather, analyze, and report on the configuration and security state of HPC clusters, maintaining ongoing situational awareness. Rather than querying each cluster independently, compliance checking can be managed from one central location.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

Methodology Guidelines on Life Cycle Assessment of Photovoltaic Electricity: 3rd Edition

Life Cycle Assessment (LCA) is a structured, comprehensive method of quantifying material- and energy-flows and their associated emissions caused in the life cycle of goods and services. The ISO 14040 and 14044 standards provide the framework for LCA. However, this framework leaves the individual practitioner with a range of choices that can affect the results and thus the conclusions of an LCA study. The current IEA guidelines were developed to provide guidance on assuring consistency, balance, and quality to enhance the credibility and reliability of the results from LCAs on photovoltaic (PV) electricity generation systems. The guidelines represent a consensus among the authors - PV LCA experts in North America, Europe, and Asia - for assumptions made on PV performance, decisions on process input and emissions allocation, methods of analysis, and reporting of the results. Guidance is given on PV-specific parameters used as inputs in LCA and on choices and assumptions in life cycle inventory (LCI) data analysis and on implementation of modeling approaches. A consistent approach towards system modeling, the functional unit, the system boundaries, water use modeling and the allocation aspects enhances the credibility of PV electricity LCA studies and enables balanced LCA-based comparisons of different electricity producing technologies. The document discusses metrics like greenhouse gas emissions (GHG), cumulative energy demand (CED), acidification potential (AP), ozone depletion potential (ODP), human toxicity, ecotoxicity and ionizing radiation. Guidance is given for the definition of the energy payback time (EPBT), the nonrenewable energy payback time (NREPBT), and the impact mitigation potentials (IMP). The indicator energy return on investment (EROI) is described in a separate International Energy Agency (IEA) PV Power Systems (PVPS) Task 12 report (Raugei et al. 2015). The guidelines on the reporting and communication of the results serve the need for producing clear, comprehensive and transparent reports.

14 SOLAR ENERGY↗
DOE OSTI2022

Phoebe: a high-performance framework for solving phonon and electron Boltzmann transport equations

Understanding the electrical and thermal transport properties of materials is critical to the design of electronics, sensors, and energy conversion devices. Computational modeling can accurately predict material properties but, in order to be reliable, requires accurate descriptions of electron and phonon states and their interactions. While first-principles methods are capable of describing the energy spectrum of each carrier, using them to compute transport properties is still a formidable task, both computationally demanding and memory intensive, requiring integration of fine microscopic scattering details for estimation of macroscopic transport properties. To address this challenge, we present Phoebe—a newly developed software package that includes the effects of electron–phonon, phonon–phonon, boundary, and isotope scattering in computations of electrical and thermal transport properties of materials with a variety of available methods and approximations. This open source C++ code combines MPI-OpenMP hybrid parallelization with GPU acceleration and distributed memory structures to manage computational cost, allowing Phoebe to effectively take advantage of contemporary computing infrastructures. We demonstrate that Phoebe accurately and efficiently predicts a wide range of transport properties, opening avenues for accelerated computational analysis of complex crystals.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Experimental Investigation of Forced Convection and Natural Circulation Cooling of a VHTR Core under Normal Operation and Accident Scenarios

This NEUP project #15-8205 entitled “Experimental Investigation of Forced Convection and Natural Circulation Cooling of a VHTR Core under Normal Operation and Accident Scenarios”, has investigated important phenomena in the safety of Very High Temperature Reactors (VHTRs) using the experimental facilities at City College of New York (CCNY) and Kansas State University (KSU), in collaboration with the Idaho State University (ISU) and Idaho National Laboratory (INL). The main objectives of this project were to investigate the forced convection and bypass flow phenomena, natural circulation flow and heat transfer, and graphite oxidation due to air ingress which could occur in a Very High Temperature Reactor (VHTR) with a prismatic core. High pressure/high temperature experiments have been conducted to obtain data that could be used for validation of VHTR design and safety analysis codes. The focus of these experiments was on the generation of benchmark data for design and off-design heat transfer for forced and natural circulation in a VHTR core. This work has built on the previous NEUP project #11-3218 which investigated forced convection and flow laminarization phenomena in a prismatic core of a VHTR and natural circulation of a pure gas under Pressurized Conduction Cooldown (PCC) and Depressurized Conduction Cooldown (DCC) conditions. Under each Task, extensive literature reviews on natural circulation, bypass flow, air ingress and graphite oxidation phenomena were conducted. In Task 1, scaling analyses were conducted by Idaho State University followed by design and construction of experimental facilities needed to conduct both bypass flow and natural circulation experiments at CCNY. Natural circulation experiments were conducted in Task 2 to investigate the air ingress phenomena, and bypass flow phenomena in Task 3, both at CCNY. In Task 4, radiation heat transfer and graphite oxidation tests were performed at Kansas State University. The experimental data were then analyzed to obtain quantitative results on natural circulation of pure gases and gas mixtures under DCC conditions, bypass flow rates, radiation heat transfer and graphite oxidation. In addition, CFD and Direct Numerical Simulations were conducted by INL and CCNY to investigate the flow laminarization phenomenon in strongly heated gas flows. The scaling analyses have shown that the key nondimensional numbers and parameters all have acceptable distortion levels principally because the CCNY facility’s test sections have representative cooling channel dimensions and are using either helium or a scalable gas such as nitrogen at representative state conditions. The natural circulation experiments involving helium and nitrogen gas mixtures at CCNY have elucidated the effect of nitrogen (simulating air) ingress into a lower plenum on the onset of natural circulation, mass flow rates and heat transfer coefficients under different power input levels in the riser section. Also, the transport of nitrogen from the lower plenum to upper plenum due to natural circulation was quantified for the first time. Nusselt number correlations for the heat transfer coefficient under natural circulation as a function of Reynolds and Prandtl numbers was also developed. The experiments at KSU revealed that prior to the onset of natural circulationin a VHTR core. This work has built on the previous NEUP project #11-3218 which investigated forced convection and flow laminarization phenomena in a prismatic core of a VHTR and natural circulation of a pure gas under Pressurized Conduction Cooldown (PCC) and Depressurized Conduction Cooldown (DCC) conditions. Under each Task, extensive literature reviews on natural circulation, bypass flow, air ingress and graphite oxidation phenomena were conducted. In Task 1, scaling analyses were conducted by Idaho State University followed by design and construction of experimental facilities needed to conduct both bypass flow and natural circulation experiments at CCNY. Natural circulation experiments were conducted in Task 2 to investigate the air ingress phenomena, and bypass flow phenomena in Task 3, both at CCNY. In Task 4, radiation heat transfer and graphite oxidation tests were performed at Kansas State University. The experimental data were then analyzed to obtain quantitative results on natural circulation of pure gases and gas mixtures under DCC conditions, bypass flow rates, radiation heat transfer and graphite oxidation. In addition, CFD and Direct Numerical Simulations were conducted by INL and CCNY to investigate the flow laminarization phenomenon in strongly heated gas flows. The scaling analyses have shown that the key nondimensional numbers and parameters all have acceptable distortion levels principally because the CCNY facility’s test sections have representative cooling channel dimensions and are using either helium or a scalable gas such as nitrogen at representative state conditions.The natural circulation experiments involving helium and nitrogen gas mixtures at CCNY have elucidated the effect of nitrogen (simulating air) ingress into a lower plenum on the onset of natural circulation, mass flow rates and heat transfer coefficients under different power input levels in the riser section. Also, the transport of nitrogen from the lower plenum to upper plenum due to natural circulation was quantified for the first time. Nusselt number correlations for the heat transfer coefficient under natural circulation as a function of Reynolds and Prandtl numbers was also developed. The experiments at KSU revealed that prior to the onset of natural circulation(ONC), molecular diffusion plays a significant role in air-ingress, however, at higher temperatures convection currents may be influencing air ingress and in-turn ONC times. Bypass flow experiments faced difficulties in the measurement of gas velocity in the main channel due to the failure of a high temperature Hot Wire Anemometer probe, so an energy balance method was instead employed to estimate the flow distribution between the main and bypass flow channels. In the graphite oxidation experiments conducted at KSU, oxidation was found to increase the thermal diffusivity of nuclear grade graphite. This change is believed to be driven by oxidation decreasing graphite sample density rather than raising the thermal conductivity. Oxidation was also shown to greatly alter graphite emissivity. If large amounts of impurities have built up within the graphite over time and have significantly increased its effective ash content, then air ingress is likely to severely inhibit the radiative heat transfer abilities of the graphite due to the formation of low emissivity, ash layers on its surface. However, if the purity of the graphite at the time of the air ingress is still close to that of its virgin specifications, the oxidation induced roughening of the graphite’s outer surface would have the effect of slightly raising its emissivity. The flow laminarization phenomenon was investigated by INL by examining the results of Direct Numerical Simulations of previous experiments, and by CCNY conducting its own DNS simulations using DOE’s Nek5000 code

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2021

Semi-supervised Bayesian Low-shot Learning

Deep neural networks (NNs) typically outperform traditional machine learning (ML) approaches for complicated, non-linear tasks. It is expected that deep learning (DL) should offer superior performance for the important non-proliferation task of predicting explosive device configuration based upon observed optical signature, a task which human experts struggle with. However, supervised machine learning is difficult to apply in this mission space because most recorded signatures are not associated with the corresponding device description, or “truth labels.” This is challenging for NNs, which traditionally require many samples for strong performance. Semi-supervised learning (SSL), low-shot learning (LSL), and uncertainty quantification (UQ) for NNs are emerging approaches that could bridge the mission gaps of few labels and rare samples of importance. NN explainability techniques are important in gaining insight into the inferential feature importance of such a complex model. In this work, SSL, LSL, and UQ are merged into a single framework, a significant technical hurdle not previously demonstrated. Exponential Average Adversarial Training (EAAT) and Pairwise Neural Networks (PNNs) are chosen as the SSL and LSL methods of choice. Permutation feature importance (PFI) for functional data is used to provide explainability via the Variable importance Explainable Elastic Shape Analysis (VEESA) pipeline. A variety of uncertainty quantification approaches are explored: Bayesian Neural Networks (BNNs), ensemble methods, concrete dropout, and evidential deep learning. Two final approaches, one utilizing ensemble methods and one utilizing evidential learning, are constructed and compared using a well-quantified synthetic 2D dataset along with the DIRSIG Megascene.

97 MATHEMATICS AND COMPUTING↗