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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.

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At least 775 records · Page 43
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Efficient Machine Learning Approach for Optimizing Scientific Computing Applications on Emerging HPC Architectures

Efficient parallel implementations of scientific applications on multi-core CPUs with accelerators such as GPUs and Xeon Phis is challenging. This requires - exploiting the data parallel architecture of the accelerator along with the vector pipelines of modern x86 CPU architectures, load balancing, and efficient memory transfer between different devices. It is relatively easy to meet these requirements for highly structured scientific applications. In contrast, a number of scientific and engineering applications are unstructured. Getting performance on accelerators for these applications is extremely challenging because many of these applications employ irregular algorithms which exhibit data-dependent control-ow and irregular memory accesses. Furthermore, these applications are often iterative with dependency between steps, and thus making it hard to parallelize across steps. As a result, parallelism in these applications is often limited to a single step. Numerical simulation of charged particles beam dynamics is one such application where the distribution of work and memory access pattern at each time step is irregular. Applications with these properties tend to present significant branch and memory divergence, load imbalance between different processor cores, and poor compute and memory utilization. Prior research on parallelizing such irregular applications have been focused around optimizing the irregular, data-dependent memory accesses and control-ow during a single step of the application independent of the other steps, with the assumption that these patterns are completely unpredictable. We observed that the structure of computation leading to control-ow divergence and irregular memory accesses in one step is similar to that in the next step. It is possible to predict this structure in the current step by observing the computation structure of previous steps. In this dissertation, we present novel machine learning based optimization techniques to address the parallel implementation challenges of such irregular applications on different HPC architectures. In particular, we use supervised learning to predict the computation structure and use it to address the control-ow and memory access irregularities in the parallel implementation of such applications on GPUs, Xeon Phis, and heterogeneous architectures composed of multi-core CPUs with GPUs or Xeon Phis. We use numerical simulation of charged particles beam dynamics simulation as a motivating example throughout the dissertation to present our new approach, though they should be equally applicable to a wide range of irregular applications. The machine learning approach presented here use predictive analytics and forecasting techniques to adaptively model and track the irregular memory access pattern at each time step of the simulation to anticipate the future memory access pattern. Access pattern forecasts can then be used to formulate optimization decisions during application execution which improves the performance of the application at a future time step based on the observations from earlier time steps. In heterogeneous architectures, forecasts can also be used to improve the memory performance and resource utilization of all the processing units to deliver a good aggregate performance. We used these optimization techniques and anticipation strategy to design a cache-aware, memory efficient parallel algorithm to address the irregularities in the parallel implementation of charged particles beam dynamics simulation on different HPC architectures. Experimental result using a diverse mix of HPC architectures shows that our approach in using anticipation strategy is effective in maximizing data reuse, ensuring workload balance, minimizing branch and memory divergence, and in improving resource utilization.

Arumugam, Kamesh↗
DOE OSTI2022

Demonstration of a fault impact reduction control module for wind turbines

Abstract. Traditionally, wind turbines in distributed applications make control decisions as isolated systems. They generally provide maximum power output during operation and manage internal faults with little consideration of the rest of the power system. Although fault detection and tolerance schemes are widely researched and implemented, controls to ameliorate such faults are uncommon in research and industry. The rapid shutdown of a wind turbine in a large transmission-connected wind plant will have a minimal impact on a large power system, but in a microgrid or isolated grid context the abrupt loss of a single wind turbine may cause grid instability and high stress on the system. This paper demonstrates a fault impact reduction control (FIRC) module for a wind turbine, which implements wider warning thresholds around fault thresholds. When the turbine crosses a warning threshold, the controller sends its predicted action to the grid controller, which facilitates the grid operator’s response to a potential wind turbine fault and then takes appropriate action to ameliorate the fault. Various test cases demonstrate the controller action under a variety of faults, and various scenarios demonstrate the grid benefit of an FIRC in both microgrid- and grid-connected contexts. The FIRC maximizes wind turbine generation and eases generation transition under a variety of fault scenarios. The FIRC module is easy to integrate with most existing controllers, just requiring derate capability, and can be easily modified to include the various warnings and thresholds that the user desires. This analysis is mainly performed in a MATLAB-Simulink-based research wind turbine model and is also implemented in the existing LabVIEW-based controller of the same research turbine at NREL.

17 WIND ENERGY↗
DOE OSTI2013

Predicting Reactor Antineutrino Emissions Using New Precision Beta Spectroscopy

Neutrino experiments at nuclear reactors are currently vital to the study of neutrino oscillations. The observed antineutrino rates at reactors are typically lower than model expectations. This observed deficit is called the “reactor neutrino anomaly”. A new understanding of neutrino physics may be required to explain this deficit, though model estimation uncertainties may also play a role in the apparent discrepancy. PNNL is currently investigating an experimental technique that promises reduced uncertainties for measured data to support these hypotheses and interpret reactor antineutrino measurements. The experimental approach is to 1) direct a proton accelerator beam on a metal target to produce a source of neutrons, 2) use spectral tailoring to modify the neutron spectrum to closely simulate the energy distribution of a power reactor neutron spectrum, 3) irradiate isotopic fission foils (235U, 238U, 239Pu, 241Pu) in this neutron spectrum so that fissions occur at energies representative of a reactor, 4) transport the beta particles released by the fission products in the foils to a beta spectrometer, 5) measure the beta energy spectrum, and 6) invert the measured beta energy spectrum to an antineutrino energy spectrum. A similar technique using a beta spectrometer and isotopic fission foils was pioneered in the 1980’s at the ILL thermal reactor. Those measurements have been the basis for interpreting all subsequent antineutrino measurements at reactors. A basic constraint in efforts to reduce uncertainties in predicting the antineutrino emission from reactor cores is any underlying limitation of the original measurements. This may include beta spectrum energy resolution, the absolute normalization of beta emission to number of fission, statistical counting uncertainties, lack of 238U data, the purely thermal nature of the IIL reactor neutrons used, etc. An accelerator-based neutron source that can be tailored to match various reactor neutron spectra provides an advantage for control in studying how changes in the neutron spectra (i.e. "in the reactor core") affects the resulting fission product beta spectrum. Furthermore, the 238U antineutrino spectrum, which has not been measured, can be studied directly because of the enhanced 1 MeV fast neutron flux available at the accelerator source. A facility such as the Project X Injector Experiment (PXIE) 30 MeV proton linear accelerator at Fermilab is being considered for this experiment. The hypothesis is that a new approach utilizing the flexibility of an accelerator neutron source with spectral tailoring coupled with a careful design of an isotopic fission target and beta spectrometer and the inversion of the beta spectrum to the neutrino spectrum will allow further reduction in the uncertainties associated with prediction of the reactor antineutrino spectrum.

Asner, David M.↗
DOE OSTI2025

Evaluating Variable-Impedance Magnetically-Insulated Transmission Lines as a Risk-Mitigation Measure for Next-Generation Pulsed Power

This project has produced the first detailed characterizations of power flow resulting from applying the “variable-impedance MITL” concept to real-life systems in Sandia’s pulsed power program (Z and next-generation pulsed power (NGPP)). We present simulation results and analyses for constant-impedance versions of both Z and NGPP and survey the operational viability of several variable-impedance re-designs in the parameter space of linear tapers. Circuit modeling (SCREAMER/Bertha) was used to pinpoint promising candidate designs, and EM-PIC (Empire) simulations were used to evaluate these candidates more rigorously. This approach was particularly successful in the Z regime which resulted in the identification of several viable variable-impedance MITL designs for each level. The approach was more challenged in the operating space NGPP occupies, producing data points that speak to a more restrictive design space due to anode plasma turn-on. In the end, we were able to converge on one viable variable-impedance design for the highest inductance line (level “F”) and one for the highest current line (level “A”). Altogether, the body of simulation evidence presented in this report suggest there does exist flexibility in operating space for magnetically-insulated transmission lines (MITLs) having variable geometric impedance to be a potential enabling technology for safely increasing current delivery (and potentially lowering stack voltage) in pulsed-power drivers by manipulating electron losses; however, operating points for a particular design must be carefully screened. Circuit and EM-PIC modeling provided consistent verdicts in safe operating regimes for operational viability, but additional physics such as anode plasma turn-on which is included in Empire but not in SCREAMER/Bertha was found to be a critical factor affecting power flow that lead to different assessments between the codes. It is not always the case that the occurrence of anode plasma caused a design to fail (some designs turned on anode plasma yet still delivered load currents meeting design targets); the details matter such as how early in the pulse anode surfaces break down (and how large a region). However, in every case that it did fail it was found that the feedback from anode plasma was the cause (i.e., turning off the anode plasma model in Empire restored agreement with the circuit model prediction). As circuit simulations represent an efficient and practical means of surveying design space compared to more computationally-expensive approaches such as EM-PIC, it could be prudent to invest in the research and development of models to include the effects of anode plasma such as ion emission in circuit codes. The variable-impedance MITL design is a new concept that enables controlled manipulation of the initial electron losses in the outer MITL and can be tested on Z today. We encourage follow-on work to explore further optimization (including alternative variable-impedance profiles, e.g., having constant dZ/dR), and to confirm the major findings presented in this report by fielding test hardware on actual Z shots.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2018

Strong correlation between stress drop and peak ground acceleration for recent M1–4 earthquakes in the San Francisco Bay Area

Theoretical and observational studies suggest that between-event variability in the median ground motions of larger ( M≥5 ) earthquakes is controlled primarily by the dynamic properties of the earthquake source, such as Brune-type stress drop. Analogous results remain equivocal for smaller events due to the lack of comprehensive and overlapping ground-motion and source-parameter datasets in this regime. Here in this paper, we investigate the relationship between peak ground acceleration (PGA) and dynamic stress drop for a new dataset of 5297 earthquakes that occurred in the San Francisco Bay area from 2002 through 2016. For each event, we measure PGA on horizontal-component channels of stations within 100 km and estimate stress drop from P-wave spectra recorded on vertical-component channels of the same stations. We then develop a nonparametric ground-motion prediction equation (GMPE) applicable for the moderate (M 1–4) earthquakes in our study region, using a mixed-effects generalization of the Random Forest algorithm. We use the Random Forest GMPE to model the joint influence of magnitude, distance, and near-site effects on observed PGA. We observe a strong correlation between dynamic stress drop and the residual PGA of each event, with the events with higher-than-expected PGA associated with higher values of stress drop. The strength of this correlation increases as a function of magnitude but remains significant even for smaller magnitude events with corner frequencies that approach the observable bandwidth of the acceleration records. Mainshock events are characterized by systematically higher stress drop and PGA than aftershocks of equivalent magnitude. Coherent local variations in the distribution of dynamic stress drop provide observational constraints to support the future development of nonergodic GMPEs that account for variations in median stress drop at different source locations.

58 GEOSCIENCES↗
DOE OSTI2018

Ground Motion and Intraevent Variability from 3D Deterministic Broadband (0-7.5 Hz) Simulations along a Nonplanar Strike-Slip Fault

In the article, we model deterministic broadband (-7.5 Hz) ground motion from an M w 7.1 bilateral strike-slip earthquake scenario with dynamic rupture propagation along a rough-fault topography embedded in a medium including small-scale velocity and density perturbations. Spectral accelerations (SAs) at periods 0.2-3 s and Arias intensity durations show a similar distance decay (at the level of 1-2 interevent standard deviations above the median) when compared to Next Generation Attenuation-West2 (NGA)-West2 ground-motion prediction equations (GMPEs) using a Q(f) power-law exponent of 0.6-0.8 above 1 Hz in models with a minimum V S of 750 m/s. With a trade-off from Q(f), the median ground motion is slightly increased by scattering from statistical models of small-scale heterogeneity with standard deviation (σ) of the perturbations at the lower end of the observed range (5%) but reduced by scattering attenuation at the upper end (10%) when using a realistic 3D background velocity model. The ground-motion variability is strongly affected by the addition of small-scale media heterogeneity, reducing otherwise large values of intraevent standard deviation closer to those of empirical observations. These simulations generally have intraevent standard deviations for SAs lower than the GMPEs for the modeled bandwidth, with an increasing trend with distance (most pronounced in low-to-moderate scattering media) near the level of observations at distances greater than 35 km from the fault. Durations for the models follow the same increasing trend with distance, in which σ~5% produces the best match to GMPE values. We find that a 3D background-velocity model reduces the pulse period into the expected range by breaking up coherent waves from directivity, generating a lognormal distribution of ground-motion residuals. These results indicate that a strongly heterogeneous medium is needed to produce realistic deterministic broadband ground motions. Finally, the addition of a thin surficial layer with low, frequency-independent Q in the model (with a minimum V S of 750 m/s) controls the high-frequency decay in energy, as measured by the parameter κ, that may be necessary to include as simulations continue to extend to higher frequencies.

Geochemistry & Geophysics↗
DOE OSTI2012

Acoustic Imaging Evaluation of Juvenile Salmonid Behavior in the Immediate Forebay of the Water Temperature Control Tower at Cougar Dam, 2010

This report presents the results of an evaluation of juvenile Chinook salmon (Oncorhynchus tshawytscha) behavior at Cougar Dam on the south fork of the McKenzie River in Oregon in 2010. The study was conducted by the Pacific Northwest National Laboratory for the U.S. Army Corps of Engineers (USACE). The overall goal of the study was to characterize juvenile salmonid behavior and movement patterns in the immediate forebay of the Water Temperature Control (WTC) tower of the dam for USACE and fisheries resource managers use in making decisions about bioengineering designs for long-term structures and/or operations to facilitate safe downstream passage for juvenile salmonids. We collected acoustic imaging (Dual-Frequency Identification Sonar; DIDSON) data from March 1, 2010, through January 31, 2011. Juvenile salmonids (hereafter, called 'fish') were present in the immediate forebay of the WTC tower throughout the study. Fish abundance index was low in early spring (<200 fish per sample-day), increased in late April, and peaked on May 19 (6,039 fish). A second peak was observed on June 6 (2904 fish). Fish abundance index decreased in early June and remained low in the summer months (<100 fish per sample-day). During the fall and winter, fish numbers varied with a peak on November 10 (1881 fish) and a minimum on December 7 (12 fish). A second, smaller, peak occurred on December 22 (607 fish). A univariate statistical analysis indicated fish abundance index (log10-transformed) was significantly (P<0.05) positively correlated with forebay elevation, velocity over the WTC tower intake gate weirs, and river flows into the reservoir. A subsequent multiple regression analysis resulted in a model (R2=0.70) predicting fish abundance (log-transformed index values) using two independent variables of mean forebay elevation and the log10 of the forebay elevation range. From the approximate fish length measurements made using the DIDSON imaging software, the average fish length during early spring 2010 was 214 ± 86 mm (standard deviation). From May through early November, the average fish length remained relatively consistent (132 ± 54 mm), after which average lengths increased to 295 ± 148 mm for mid-November though early December. From mid-December through January the average fish length decreased to 151 76 mm. Milling in front of the WTC tower was the most common fish behavior observed throughout the study period. Traversing along the front of the tower, east-to-west and west-to-east, was the next common behavior. The percentage of fish events showing movement from the forebay to the tower or from the tower to the forebay was generally low throughout the spring, summer, and early fall (0 to 30% for both directions combined, March through early November). From mid-November 2010 through the end of the study (January 31, 2011), the combined percentages of fish moving into and out of the tower were higher (25 to 70%) than during previous months of the study. Schooling behavior was most distinct in the spring. Schooling events were present in 30 to 96% of the fish events during that period, with a peak on May 19. Schooling events were also present in the summer, but at lower numbers. With the exception of some schooling in mid-December, few to no schooling events were observed in the fall and winter months. Diel distributions for schooling fish during spring and fall months indicate schooling was concentrated during daylight hours and no schooling was observed at night. However, in December, schooling occurred at night, after midnight, and during daylight hours. Predator activity, most likely bull trout or rainbow trout according to a USACE biologist, was observed during late spring, when fish abundance index and schooling were highest for the year, and again in the fall months when fish events increased from a summer low. No predator activity was observed in the summer, and little activity occurred during the winter months.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2013

FORMULATION OF NON-STEADY-STATE DUST FORMATION PROCESS IN ASTROPHYSICAL ENVIRONMENTS

The non-steady-state formation of small clusters and the growth of grains accompanied by chemical reactions are formulated under the consideration that the collision of key gas species (key molecule) controls the kinetics of dust formation process. The formula allows us to evaluate the size distribution and condensation efficiency of dust formed in astrophysical environments. We apply the formulation to the formation of C and MgSiO{sub 3} grains in the ejecta of supernovae, as an example, to investigate how the non-steady effect influences the formation process, condensation efficiency f{sub con,{sub ∞}}, and average radius a{sub ave,{sub ∞}} of newly formed grains in comparison with the results calculated with the steady-state nucleation rate. We show that the steady-state nucleation rate is a good approximation if the collision timescale of key molecule τ{sub coll} is much smaller than the timescale τ{sub sat} with which the supersaturation ratio increases; otherwise the effect of the non-steady state becomes remarkable, leading to a lower f{sub con,{sub ∞}} and a larger a{sub ave,{sub ∞}}. Examining the results of calculations, we reveal that the steady-state nucleation rate is applicable if the cooling gas satisfies Λ ≡ τ{sub sat}/τ{sub coll} ∼> 30 during the formation of dust, and find that f{sub con,{sub ∞}} and a{sub ave,{sub ∞}} are uniquely determined by Λ{sub on} at the onset time t{sub on} of dust formation. The approximation formulae for f{sub con,{sub ∞}} and a{sub ave,{sub ∞}} as a function of Λ{sub on} could be useful in estimating the mass and typical size of newly formed grains from observed or model-predicted physical properties not only in supernova ejecta but also in mass-loss winds from evolved stars.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

Integral Reactor Containment Condensation Model and Experimental Validation

This NEUP funded project, NEUP 12-3630, is for experimental, numerical and analytical studies on high-pressure steam condensation phenomena in a steel containment vessel connected to a water cooling tank, carried out at Oregon State University (OrSU) and the University of Wisconsin at Madison (UW-Madison). In the three years of investigation duration, following the original proposal, the planned tasks have been completed: (1) Performed a scaling study for the full pressure test facility applicable to the reference design for the condensation heat transfer process during design basis accidents (DBAs), modified the existing test facility to route the steady-state secondary steam flow into the high pressure containment for controllable condensation tests, and extended the operations at negative gage pressure conditions (OrSU). (2) Conducted a series of DBA and quasi-steady experiments using the full pressure test facility to provide a reliable high pressure condensation database (OrSU). (3) Analyzed experimental data and evaluated condensation model for the experimental conditions, and predicted the prototypic containment performance under accidental conditions (UW-Madison). A film flow model was developed for the scaling analysis, and the results suggest that the 1/3 scaled test facility covers large portion of laminar film flow, leading to a lower average heat transfer coefficient comparing to the prototypic value. Although it is conservative in reactor safety analysis, the significant reduction of heat transfer coefficient (50%) could under estimate the prototypic condensation heat transfer rate, resulting in inaccurate prediction of the decay heat removal capability. Further investigation is thus needed to quantify the scaling distortion for safety analysis code validation. Experimental investigations were performed in the existing MASLWR test facility at OrST with minor modifications. A total of 13 containment condensation tests were conducted for pressure ranging from 4 to 21 bar with three different static inventories of non-condensable gas. Condensation and heat transfer rates were evaluated employing several methods, notably from measured temperature gradients in the HTP as well as measured condensate formation rates. A detailed mass and energy accounting was used to assess the various measurement methods and to support simplifying assumptions required for the analysis. Condensation heat fluxes and heat transfer coefficients are calculated and presented as a function of pressure to satisfy the objectives of this investigation. The major conclusions for those tests are summarized below: (1) In the steam blow-down tests, the initial condensation heat transfer process involves the heating-up of the containment heat transfer plate. An inverse heat conduction model was developed to capture the rapid transient transfer characteristics, and the analysis method is applicable to SMR safety analysis. (2) The average condensation heat transfer coefficients for different pressure conditions and non-condensable gas mass fractions were obtained from the integral test facility, through the measurements of the heat conduction rate across the containment heat transfer plate, and from the water condensation rates measurement based on the total energy balance equation. 15 (3) The test results using the measured HTP wall temperatures are considerably lower than popular condensation models would predict mainly due to the side wall conduction effects in the existing MASLWR integral test facility. The data revealed the detailed heat transfer characteristics of the model containment, important to the SMR safety analysis and the validation of associated evaluation model. However this approach, unlike separate effect tests, cannot isolate the condensation heat transfer coefficient over the containment wall, and therefore is not suitable for the assessment of the condensation heat transfer coefficient against system pressure and noncondensable gas mass fraction. (4) The average condensation heat transfer coefficients measured from the water condensation rates through energy balance analysis are appropriate, however, with considerable uncertainties due to the heat loss and temperature distribution on the containment wall. With the consideration of the side wall conduction effects, the results indicate that the measured heat transfer coefficients in the tests is about 20% lower than the prediction of Dehbi’s correlation, mainly due to the side wall conduction effects. The investigation also indicates an increase in the condensation heat transfer coefficient at high containment pressure conditions, but the uncertainties invoked with this method appear to be substantial. (5) Non-condensable gas in the tests has little effects on the condensation heat transfer at high elevation measurement ports. It does affect the bottom measurements near the water level position. The results suggest that the heavier non-condensable gas is accumulated in the lower portion of the containment due to stratification in the narrow containment space. The overall effects of the non-condensable gas on the heat transfer process should thus be negligible for tall containments of narrow condensation spaces in most SMR designs. Therefore, the previous correlations with noncondensable gas effects are not appropriate to those small SMR containments due to the very poor mixing of steam and non-condensable gas. The MELCOR simulation results agree with the experimental data reasonably well. However, it is observed that the MELCOR overpredicts the heat flux for all analyzed tests. The MELCOR predicts that the heat fluxes for CCT’s approximately range from 30 to 45 kW/m2 whereas the experimental data (averaged) ranges from about 25 to 40 kW/m2. This may be due to the limited availability of liquid film models included in MELCOR. Also, it is believed that due to complex test geometry, measured temperature gradients across the heat transfer plate may have been underestimated and thus the heat flux had been underestimated. The MELCOR model predicts a film thickness on the order of 100 microns, which agrees very well with film flow model developed in this study for scaling analysis. However, the expected differences in film thicknesses for near vacuum and near atmospheric test conditions are not significant. Further study on the behavior of condensate film is expected to refine the simulation results. Possible refinements include but are not limited to, the followings: CFD simulation focusing on the liquid film behavior and benchmarking with experimental analyses for simpler geometries. 16 1 INTRODUCTION This NEUP funded project, NEUP 12-3630, is for experimental, numerical and analytical studies on high-pressure steam condensation phenomena in a steel containment vessel connected to a water cooling tank, carried out at Oregon State University (OrSU) and the University of Wisconsin at Madison (UW-Madison). The experimental results are employed to validate the containment condensation model in reactor containment system safety analysis code for integral SMRs. Such a containment condensation model is important to demonstrate the adequate cooling. In the three years of investigation, following the original proposal, the following planned tasks have been completed: (1) Performed a scaling study for the full pressure test facility applicable to the reference design for the condensation heat transfer process during design basis accidents (DBAs), modified the existing test facility to route the steady-state secondary steam flow into the high pressure containment for controllable condensation tests, and extended the operations at negative gage pressure conditions (OrSU). (2) Conducted a series of DBA and quasi-steady experiments using the full pressure test facility to provide a reliable high pressure condensation database (OrSU). (3) Analyzed experimental data and evaluated condensation model for the experimental conditions, and predicted the prototypic containment performance under accidental conditions (UW-Madison). The results are applicable to integral Small Modular Reactor (SMR) designs, including NuScale, mPower, Westinghouse SMR, Holtec-160 and other integral reactors with small containments of relatively high pressures under accidental conditions. Testing has been conducted at the OrSU laboratory in the existing MASLWR (Multi-Application Small Light Water Reactor) integral test facility sponsored by the US Department of Energy. Its highpressure stainless steel containment model (~2 MPa) is scaled to the NuScale SMR currently under development at NuScale Power, Inc.. Minor modifications to the model containment have been made to control the non-condensable gas fraction and to utilize the secondary loop stable steam flow for condensation testing. UW-Madison has developed a containment condensation model, which leveraged previous validated containment heat transfer work carried out at UW-Madison, and extended the range of applicability of the model to integral SMR designs that utilize containment vessels of high heat transfer efficiencies. In this final report, the research background and literature survey are presented in Chapter 2 and 3, respectively. The test facility description and modifications are summarized in Chapter 4, and the scaling analysis is introduced in Chapter 5. The tests description, procedures, and data analysis are presented in Chapter 6, while the numerical modeling is presented in Chapter 7, followed by a conclusion section in Chapter 8.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2025

Kinetic Modeling of Secondary Organic Aerosol in a Weather-Chemistry Model: Parameterizations, Processes, and Predictions for GOAmazon

Secondary organic aerosol (SOA) forms and evolves in the atmosphere through many pathways and processes, over diverse spatial and time scales. Hence, there is a need to represent these widely-varying kinetic processes in large-scale atmospheric models to allow for accurate predictions of the abundance, properties, and impacts of SOA. In this work, we integrated a kinetic, process-level model (simpleSOM-MOSAIC) into a weather-chemistry model (WRF-Chem) to simulate the oxidation chemistry and microphysics of atmospheric SOA. simpleSOM-MOSAIC simulates multigenerational gas-phase chemistry, autoxidation reactions, heterogeneous oxidation, oligomerization, and phase-state-influenced gas/particle partitioning of SOA. As a case study, the integrated WRF-Chem-simpleSOM-MOSAIC (WC-SSM) model was used to simulate the photochemical evolution downwind of a large city (Manaus, Brazil) in the Amazon and, in turn, study the anthropogenic and biogenic interactions in an otherwise pristine environment. Consistent with previous work, we found that OA was enhanced by up to a factor of four in the urban plume due to elevated hydroxyl radical (OH) concentrations, relative to the background, and that this OA was dominated by SOA from biogenic precursors (80%). Further, in addition to accurately simulating the OA enhancement in the urban plume, the model reproduced the magnitude of the OA oxygen-to-carbon (O:C) ratio and broadly tracked the evolution of the aerosol size distribution. Our work highlights the importance of including an integrated, kinetic representation of SOA processes in an atmospheric model

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Orientation-Dependent Surface Faceting in UO{sub 2}

The surface behavior of UO{sub 2} plays an important role throughout the lifetime of this widely-used commercial nuclear fuel, from manufacturing to waste storage. UO{sub 2} surface properties affect fuel swelling behavior by determining the morphology, size and distribution of fission gas bubbles. Additionally, UO{sub 2} surface characteristics influence fracture behavior, which is controlled by the thermodynamics of fracture surfaces. Therefore, detailed understanding of the fundamental surface behavior will help advance prediction of the fuel performance of UO{sub 2}. Due to significant anisotropy in surface tension, faceting features form after annealing in both UO{sub 2} and many other crystalline materials. Knowledge of the correlation between crystallographic orientation and surface faceting features will expand the fundamental knowledge of UO{sub 2} surface characteristics, leading to a better understanding of fission gas swelling and fracture mechanisms. Inherent characterization technique limited previous studies on the crystallographic orientation of UO{sub 2} surface facets to low Miller index surfaces in single crystal specimens. In this study, synchrotron Laue microdiffraction was utilized to examine the crystallographic orientation of grains on the coarse surface of a polycrystalline UO{sub 2} specimen. The results were then compared with the surface morphology, obtained from scanning electron microscopy (SEM), so that a general correlation between the surface faceting features and crystallographic orientation in UO{sub 2} can be established. Both the fundamental surface characteristics and the crystallographic orientation measurements obtained in this study help advance the experiment validation of MARMOT, a mesoscale multi-physics code that predicts the coevolution of microstructure and properties within reactor fuel during its lifetime in the reactor. The MARMOT code is an indispensable component of the MOOSE-BISON-MARMOT (MBM) code suite that has been developed by Idaho National Laboratory to enable next generation fuel performance modeling capability as a part of the Nuclear Energy Advanced Modeling and Simulation (NEAMS) Program Fuels Product Line (FPL). In this study, the surface-faceting features of UO{sub 2} were found to be dominated by the triple-plane structure and its variants. With this knowledge, by measuring the directions of the <110> edges, the crystallographic orientation of a surface UO{sub 2} grain can be precisely deduced in most regions of the standard stereogram triangle (SST) of the surface normal. (authors)

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Impact of Drought on Ecohydrology of Southern California Grassland and Shrubland

Abstract Through their rooting profiles and water demands, plants affect the distribution of water in the soil profile. Simultaneously, soil water content controls plant development and interactions within and between plant communities. These plant-soil water feedbacks might vary across plant communities with different rooting depths and species composition. In semiarid environments, understanding these differences will be essential to predict how ecosystems will respond to drought, which may become more frequent and severe with climate change. In this study, we tested how plant-soil water feedbacks responded to drought in two contrasting ecosystem types—grassland and shrubland—in the coastal foothills of southern California. During years 5–8 of an ongoing precipitation manipulation experiment, we measured changes in plant communities and soil moisture up to 2 m depth. We observed different water use patterns in grassland and shrubland communities with distinct plant functional types and water use strategies. Drought treatment did not affect perennial, deep-rooted shrubs because they could access deep soil water pools. However, mid-rooted shrubs were sensitive to drought and experienced decreased productivity and die-off. As a result, water content actually increased with drought at soil depths from 50–150 cm. In grassland, biomass production by annual species, including annual grasses and forbs, declined with drought, resulting in lower water uptake from the surface soil layer. An opportunistic “live fast, die young“ life strategy allowed these species to recover quickly once water availability increased. Our results show how drought interacts with plant community composition to affect the soil water balance of semiarid ecosystems, information that could be integrated into global scale models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2011

Reliable algorithms for power system analysis in the presence of data uncertainties

A robust and reliable power flow analysis represents an essential requirement for many power systems applications as far as network optimization, voltage control, state estimation, and service restoration are concerned. The most common power flow approach, referred to here as a deterministic power flow (PLF), requires precise or 'crisp' values chosen by the analyst for each input variable. The solution provides precise network voltages and flows through each line. The specified values rest upon assumptions about the operating condition derived from historical measurements or predictions about future conditions and thus, cannot be considered accurate. Even in the case where the inputs are based on measurements, inaccuracies arise from time-skew problems, three-phase unbalance, static modeling approximations of dynamic components (e.g., transformer tap changers), variations in line parameters, and so on. The advent of deregulation and competitive power markets will only exacerbate this problem as well-known generation patterns change, loading becomes less predictable and the transmission paths grow more diverse. Conventional methodologies proposed in literature address tolerance analysis of power flow solution by means of detailed probabilistic methods, accounting for the variability and stochastic nature of the input data, and sampling based approaches. In particular uncertainty propagation using sampling based methods, such as the Monte Carlo, requires several model runs that sample various combinations of input values. Since the number of model runs can sometimes be very large, the required computer resources can sometimes be prohibitively expensive resulting in substantial computational demands. As far as probabilistic methods are concerned, they represent a useful tool, especially for planning studies, but, as evidenced by the many discussions reported in literature, they could reveal some shortcomings principally arising from: (1) the non-normal distribution and the statistical dependence of the input data; and (2) the difficulty arising in accurately identifying probability distributions for some input data, such as the power generated by wind or photovoltaic generators. All these could result in time consuming computations with several limitations in practical applications especially in power flow analysis of complex power networks. In order to try and overcome some of these limitations, obtaining thereby comprehensive power flow solution tolerance analysis at adequate computational costs, self validated computation could play a crucial role. Armed with such a vision, this chapter will analyze two advanced techniques for power flow analysis in the presence of data uncertainty namely the boundary power flow and the affine arithmetic power flow.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2016

CLASH-VLT: testing the nature of gravity with galaxy cluster mass profiles

We use high-precision kinematic and lensing measurements of the total mass profile of the dynamically relaxed galaxy cluster MACS J1206.2-0847 at z=0.44 to estimate the value of the ratio η=Ψ/Φ between the two scalar potentials in the linear perturbed Friedmann-Lemaitre-Robertson-Walker metric. An accurate measurement of this ratio, called anisotropic stress, could show possible, interesting deviations from the predictions of the theory of General Relativity, according to which Ψ should be equal to Φ. Complementary kinematic and lensing mass profiles were derived from exhaustive analyses using the data from the Cluster Lensing And Supernova survey with Hubble (CLASH) and the spectroscopic follow-up with the Very Large Telescope (CLASH-VLT). Whereas the kinematic mass profile tracks only the time-time part of the perturbed metric (i.e. only Φ), the lensing mass profile reflects the contribution of both time-time and space-space components (i.e. the sum Φ+Ψ). We thus express η as a function of the mass profiles and perform our analysis over the radial range 0.5 Mpc≤ r≤ r{sub 200}=1.96 Mpc. Using a spherical Navarro-Frenk-White mass profile, which well fits the data, we obtain η(r{sub 200})=1.01 {sub −0.28}{sup +0.31} at the 68% C.L. We discuss the effect of assuming different functional forms for mass profiles and of the orbit anisotropy in the kinematic reconstruction. Interpreting this result within the well-studied f(R) modified gravity model, the constraint on η translates into an upper bound to the interaction length (inverse of the scalaron mass) smaller than 2 Mpc. This tight constraint on the f(R) interaction range is however substantially relaxed when systematic uncertainties in the analysis are considered. Our analysis highlights the potential of this method to detect deviations from general relativity, while calling for the need of further high-quality data on the total mass distribution of clusters and improved control on systematic effects.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

Projected decreases in future marine export production: the role of the carbon flux through the upper ocean ecosystem

Here, accurate projections of marine particle export production (EP) are crucial for predicting the response of the marine carbon cycle to climate change, yet models show a wide range in both global EP and their responses to climate change. This is, in part, due to EP being the net result of a series of processes, starting with net primary production (NPP) in the sunlit upper ocean, followed by the formation of particulate organic matter and the subsequent sinking and remineralisation of these particles, with each of these processes responding differently to changes in environmental conditions. Here, we compare future projections in EP over the 21st century, generated by four marine ecosystem models under the high emission scenario Representative Concentration Pathways (RCP) 8.5 of the Intergovernmental Panel on Climate Change (IPCC), and determine the processes driving these changes. The models simulate small to modest decreases in global EP between -1 and -12%. Models differ greatly with regard to the drivers causing these changes. Among them, the formation of particles is the most uncertain process with models not agreeing on either magnitude or the direction of change. The removal of the sinking particles by remineralisation is simulated to increase in the low and intermediate latitudes in three models, driven by either warming-induced increases in remineralisation or slower particle sinking, and show insignificant changes in the remaining model. Changes in ecosystem structure, particularly the relative role of diatoms matters as well, as diatoms produce larger and denser particles that sink faster and are partly protected from remineralisation. Also this controlling factor is afflicted with high uncertainties, particularly since the models differ already substantially with regard to both the initial (present-day) distribution of diatoms (between 11–94% in the Southern Ocean) and the diatom contribution to particle formation (0.6–3.8 times higher than their contribution to biomass). As a consequence, changes in diatom concentration are a strong driver for EP changes in some models but of low significance in others. Observational and experimental constraints on ecosystem structure and how the fixed carbon is routed through the ecosystem to produce export production are urgently needed in order to improve current generation ecosystem models and their ability to project future changes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Estimating Total Methane Emissions from the Denver-Julesburg Basin Using Bottom-Up Approaches

Methane is a powerful greenhouse gas with a 25 times higher 100-year warming potential than carbon dioxide and is a target for mitigation to achieve climate goals. To control and curb methane emissions, estimates are required from the sources and sectors which are typically generated using bottom-up methods. However, recent studies have shown that national and international bottom-up approaches can significantly underestimate emissions. In this study, we present three bottom-up approaches used to estimate methane emissions from all emission sectors in the Denver-Julesburg basin, CO, USA. Our data show emissions generated from all three methods are lower than historic measurements. A Tier 1/2 approach using IPCC emission factors estimated 2022 methane emissions of 358 Gg (0.8% of produced methane lost by the energy sector), while a Tier 3 EPA-based approach estimated emissions of 269 Gg (0.2%). Using emission factors informed by contemporary and region-specific measurement studies, emissions of 212 Gg (0.2%) were calculated. The largest difference in emissions estimates were a result of using the Mechanistic Air Emissions Simulator (MAES) for the production and transport of oil and gas in the DJ basin. The MAES accounts for changes to regulatory practice in the DJ basin, which include comprehensive requirements for compressors, pneumatics, equipment leaks, and fugitive emissions, which were implemented to reduce emissions starting in 2014. The measurement revealed that normalized gas loss is predicted to have been reduced by a factor of 20 when compared to 10-year-old normalization loss measurements and a factor of 10 less than a nearby oil and production area (Delaware basin, TX); however, we suggest that more measurements should be made to ensure that the long-tail emission distribution has been captured by the modeling. This study suggests that regulations implemented by the Colorado Department of Public Health and Environment could have reduced emissions by a factor of 20, but contemporary regional measurements should be made to ensure these bottom-up calculations are realistic.

03 NATURAL GAS↗
DOE OSTI2012

Integrated Radiation Transport and Nuclear Fuel Performance for Assembly-Level Simulations

The Advanced Multi-Physics (AMP) Nuclear Fuel Performance code (AMPFuel) is focused on predicting the temperature and strain within a nuclear fuel assembly to evaluate the performance and safety of existing and advanced nuclear fuel bundles within existing and advanced nuclear reactors. AMPFuel was extended to include an integrated nuclear fuel assembly capability for (one-way) coupled radiation transport and nuclear fuel assembly thermo-mechanics. This capability is the initial step toward incorporating an improved predictive nuclear fuel assembly modeling capability to accurately account for source-terms, such as neutron flux distribution, coolant conditions and assembly mechanical stresses, of traditional (single-pin) nuclear fuel performance simulation. A novel scheme is introduced for transferring the power distribution from the Scale/Denovo (Denovo) radiation transport code (structured, Cartesian mesh with smeared materials within each cell) to AMPFuel (unstructured, hexagonal mesh with a single material within each cell), allowing the use of a relatively coarse spatial mesh (10 million elements) for the radiation transport and a fine spatial mesh (3.3 billion elements) for thermo-mechanics with very little loss of accuracy. With this novel capability, AMPFuel was used to model an entire 1717 pressurized water reactor fuel assembly with many of the features resolved in three dimensions (for thermo-mechanics and/or neutronics). A full assembly calculation was executed on Jaguar using 40,000 cores in under 10 hours to model over 160 billion degrees of freedom for 10 loading steps. The single radiation transport calculation required about 50% of the time required to solve the thermo-mechanics with a single loading step, which demonstrates that it is feasible to incorporate, in a single code, a high-fidelity radiation transport capability with a high-fidelity nuclear fuel thermo-mechanics capability and anticipate acceptable computational requirements. The results of the full assembly simulation clearly show the axial, radial, and azimuthal variation of the neutron flux, power, temperature, and deformation of the assembly, highlighting behavior that is neglected in traditional axisymmetric fuel performance codes that do not account for assembly features, such as guide tubes and control rods.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

Application of an Embedded Fracture and Borehole Modeling Approach to the Understanding of EGS Collab Experiment 1

EGS Collab is a series of meso-scale experiments and associated numerical simulation activities being funded by the United States Department of Energy, Geothermal Technologies Office (GTO) to investigate enhanced geothermal system processes under in-situ stress and slightly elevated temperature conditions. This project is designed to provide scientists and engineers with immediate access to impermeable rock at scales larger than possible in the laboratory, but generally smaller than those for commercial production. Immediate access to rock is provided via the existing drifts of the former Homestake Gold Mine, now operated as the Sanford Underground Research Facility in Lead, South Dakota. The objectives of the EGS Collab project are to develop well controlled fracture networks between injector and producer boreholes using normal and shear stimulation for permeability enhancement. The first experimental site was located off the West Access drift on the 4850 Level (4850 feet below ground surface) in phyllite of the Precambrian Poorman formation, and involved the creation of a fracture network comprising a combination of hydraulic and natural fractures. A second experimental site is now being considered near the battery alcove on the 4100 Level in amphibolite and rhyolite of the Yates Unit. Data generated during these experiments will be compared against predictions of a suite of computer codes specifically designed to solve problems involving coupled thermal, hydrological, geomechanical, and geochemical processes. Comparisons between experimental and numerical simulation results will provide code developers with direction for improvements and verification of process models, build confidence in the suite of available numerical tools, and ultimately identify critical future development needs for the geothermal modeling community. Moreover, conducting thorough comparisons of models, modelling approaches, measurement approaches and measured data, via the EGS Collab project, will serve to identify techniques that are most likely to succeed at the Frontier Observatory for Research in Geothermal Energy (FORGE), the GTO’s flagship EGS research effort. Experiment 1 has comprised a series of successful tests, including a long-term chilled-water circulation test, but the testbed has two atypical EGS elements. Active ventilation in the adjacent drift over a 50-year period cooled the testbed rock mass and hydraulic fracturing intersected monitoring boreholes making them conduits for fluid flow. Numerical simulations executed in support of the design of the EGS Collab Experiment 1, computed a radial temperature distribution and stress gradient orthogonal to the drift axis, resulting in the forecast of an oblong hydraulic fracture geometry, extended in the direction of the drift from the stimulation borehole. This paper describes the numerical simulation of long-term chilled-water circulation test with an embedded fracture and borehole modeling approach. The principal objective of the simulation work is show agreement between experimental observations in terms of production fluid temperatures, monitoring borehole temperatures, injection and production pressures, and tracer recoveries using a single conceptual model for the fracture network, using characterization and monitoring data generally available for EGS. A secondary objective is to improve the numerical simulation result comparisons with additional data available from the broader monitoring equipment within the testbed versus deeper, hotter, and more remote EGS. One complicating factor for comparisons between the numerical simulation results and experimental observations, is the Joule-Thomson heating associated with large pressure drops across the fracture network.

numerical simulation, embedded fractures and boreh↗