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At least 1,225 records · Page 68

Combined Error and Uncertainty Estimates for CFD Problems

Given input sources of uncertainty, non-intrusive uncertainty propagation methods quantify the uncertainty in output quantities of interest (QoI) by performing a nite number of CFD (Computational Fluid Dynamics) instance realizations needed in the calculation of output statistics. It is well known that this introduces multiple sources of error. CFD codes often utilize finite-dimensional approximation (grids, basis functions, etc.) thus incurring CFD numerical errors often approximately reinterpreted as a statistical bias. Uncertainty propagation methods calculate uncertainty statistics for output quantities of interest using a numerical method (e.g. deterministic quadrature, sampling, etc.) thus incurring UQ (Uncertainty Quantification) numerical errors. Importance of quantifying these errors in large scale scientific computing: How accurate is an output statistic?; How should additional computational resources be invested to further reduce the error in a statistic?

Posteriori↗

Ozone Production and Precursor Emission from Wildfires in Africa

Tropospheric ozone (O3) negatively impacts human health and is also a greenhouse gas. It is formed photochemically by reactions of nitrogen oxides (NOx) and volatile organic compounds (VOCs), of which wildfires are an important source. This study presents data from research flights sampling wildfires in West and Central African savannah regions, both close to the fires and after the emissions had been transported several days over the tropical North Atlantic Ocean. Emission factors (EFs) in g kg-1 for NOx (as NO), six VOCs and formaldehyde were calculated from enhancement to mole fractions in data taken close to the fires. For NOx, the emission factor was calculated as 2.05±0.43 g kg-1 for Senegal and 1.20±0.28 g kg-1 for Uganda, both higher than the average value of 1.13±0.6 g kg-1 for previous studies of African savannah regions. For most VOCs (except acetylene), EFs in Uganda were lower by factors of 20-50% compared to Senegal, with almost all the values below those in the literature. O3 enhancement in the fire plumes was investigated by examining the ΔO3/ΔCO enhancement ratio, with values ranging from 0.07 - 0.14 close to the fires up to 0.25 for measurements taken over the Atlantic Ocean up to 200 hours downwind. In addition, measurements of O3 and its precursors were compared to the output of a global chemistry transport model (GEOS-CF) for the flights over the Atlantic Ocean. Normalised mean bias (NMB) comparison between the measured and modelled data was good outside of the fire plumes, with CO showing a model under-prediction of 4.6% and O3 a slight over-prediction of 0.7% (both within the standard deviation of the data). For NOx the agreement was poorer, with an under-prediction of 9.9% across all flights. Inside the fire plumes the agreement between modelled and measured values is worse, with the model being biased significantly lower for all three species. In total across all flights, there was an under-prediction of 29.4%, 16.5% and 37.5% for CO, O3 and NOx respectively. Finally, the measured ΔO3/ΔCO enhancement ratios were compared those in the model for the equivalent flight data, with the model showing a lower value of 0.17±0.03 compared to an observed value of 0.29±0.05. The results detailed here show that the O3 burden to the North Atlantic Ocean from African wildfires may be underestimated and that further study is required to better study the O3 precursor emissions and chemistry.

James D Lee↗

A High-Granularity Approach to Modeling Energy Consumption and Savings Potential in the U.S. Residential Building Stock

Building simulations are increasingly used in various applications related to energy efficient buildings. For individual buildings, applications include: design of new buildings, prediction of retrofit savings, ratings, performance path code compliance and qualification for incentives. Beyond individual building applications, larger scale applications (across the stock of buildings at various scales: national, regional and state) include: codes and standards development, utility program design, regional/state planning, and technology assessments. For these sorts of applications, a set of representative buildings are typically simulated to predict performance of the entire population of buildings. Focusing on the U.S. single-family residential building stock, this paper will describe how multiple data sources for building characteristics are combined into a highly-granular database that preserves the important interdependencies of the characteristics. We will present the sampling technique used to generate a representative set of thousands (up to hundreds of thousands) of building models. We will also present results of detailed calibrations against building stock consumption data.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

A Mechanistic Reliability Assessment of RVACS and Metal Fuel Inherent Reactivity Feedbacks

GE Hitachi Nuclear Energy (GEH) and Argonne National Laboratory (Argonne) participated in a two year collaboration to modernize and update the probabilistic risk assessment (PRA) for the PRISM sodium fast reactor. At a high level, the primary outcome of the project was the development of a next-generation PRA that is intended to enable risk-informed prioritization of safety- and reliability-focused research and development. A central Argonne task during this project was a reliability assessment of passive safety systems, which included the Reactor Vessel Auxiliary Cooling System (RVACS) and the inherent reactivity feedbacks of the metal fuel core. Both systems were examined utilizing a methodology derived from the Reliability Method for Passive Safety Functions (RMPS), with an emphasis on developing success criteria based on mechanistic system modeling while also maintaining consistency with the Fuel Damage Categories (FDCs) of the mechanistic source term assessment. This paper provides an overview of the reliability analyses of both systems, including highlights of the FMEAs, the construction of best-estimate models, uncertain parameter screening and propagation, and the quantification of system failure probability. In particular, special focus is given to the methodologies to perform the analysis of uncertainty propagation and the determination of the likelihood of violating FDC limits. Additionally, important lessons learned are also reviewed, such as optimal sampling methodologies for the discovery of low likelihood failure events and strategies for the combined treatment of aleatory and epistemic uncertainties.

Grabaskas, David↗

Numerical Uncertainty Estimation for Stochastic Particle-in-Cell Simulations Applied to Verification and Validation.

Systematic veri cation and validation (V&V) is necessary to establish the credibility for high consequence simulations. In this paper, we focus on a radiation-induced plasma experimental validation exercise for simulations which uses both numerical error estimation and input parameter uncertainty quanti cation to provide a direct comparison between Particle-In-Cell (PIC) plasma simulations and experiments. This approach demonstrates how careful validation can uncover missing physics in the simulation. Three di erent validation examples are shown; a vacuum space charge limited cavity, a gas lled space charge limited cavity, and a vacuum non space charge limited cavity. Two of the example are picked to show the importance of error estimation in uncovering inaccuracy/incomplete simulation models. We also report on a newly-developed numerical error estimation approach, StREEQ, which is a notable improvement to past approaches. In the StREEQ approach, a multi- tting scheme based on L 1 , L 2 , and L$\infty$ error norms and alternate weightings is used to propagate uncertainties in the relative importance of outliers and coarse/re ned discretization levels. Bootstrap sampling is used to represent the stochasticity in the response data. The resulting method appears to robustly and conservatively predict the fully-converged response within estimated numerical error bounds for stochastic simulations. The StREEQ approach is demonstrated on two related prototype electron diode problems, and preliminary results are reported for a radiation-induced plasma simulation.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

A High-Granularity Approach to Modeling Energy Consumption and Savings Potential in the U.S. Residential Building Stock: Preprint

Building simulations are increasingly used in various applications related to energy efficient buildings. For individual buildings, applications include: design of new buildings, prediction of retrofit savings, ratings, performance path code compliance and qualification for incentives. Beyond individual building applications, larger scale applications (across the stock of buildings at various scales: national, regional and state) include: codes and standards development, utility program design, regional/state planning, and technology assessments. For these sorts of applications, a set of representative buildings are typically simulated to predict performance of the entire population of buildings. Focusing on the U.S. single-family residential building stock, this paper will describe how multiple data sources for building characteristics are combined into a highly-granular database that preserves the important interdependencies of the characteristics. We will present the sampling technique used to generate a representative set of thousands (up to hundreds of thousands) of building models. We will also present results of detailed calibrations against building stock consumption data.

building stock↗

Active layer hydrology in an arctic tundra ecosystem: quantifying water sources and cycling using water stable isotopes

Climate change and thawing permafrost in the Arctic will significantly alter landscape hydro-geomorphology and the distribution of soil moisture, which will have cascading effects on climate feedbacks (CO 2 and CH 4 ) and plant and microbial communities. Fundamental processes critical to predicting active layer hydrology are not well understood. This study applied water stable isotope techniques (δ 2 H and δ 18 O) to infer sources and mixing of active layer waters in a polygonal tundra landscape in Barrow, Alaska (USA), in August and September of 2012. Results suggested that winter precipitation did not contribute substantially to surface waters or subsurface active layer pore waters measured in August and September. Summer rain was the main source of water to the active layer, with seasonal ice melt contributing to deeper pore waters later in the season. Surface water evaporation was evident in August from a characteristic isotopic fractionation slope (δ 2 H vs δ 18 O). Freeze-out isotopic fractionation effects in frozen active layer samples and textural permafrost were indistinguishable from evaporation fractionation, emphasizing the importance of considering the most likely processes in water isotope studies, in systems where both evaporation and freeze-out occur in close proximity. The fractionation observed in frozen active layer ice was not observed in liquid active layer pore waters. Such a discrepancy between frozen and liquid active layer samples suggests mixing of meltwater, likely due to slow melting of seasonal ice. In conclusion, this research provides insight into fundamental processes relating to sources and mixing of active layer waters, which should be considered in process-based fine-scale and intermediate-scale hydrologic models.

54 ENVIRONMENTAL SCIENCES↗

Simulated Irradiation of Samples in HFIR for use as Possible Test Materials in the MPEX (Material Plasma Exposure Experiment) Facility

The importance of Plasma Material Interaction (PMI) is a major concern in fusion reactor design and analysis. The Material-Plasma Exposure eXperiment (MPEX) facility will explore PMI under fusion reactor plasma conditions. Samples with accumulated displacements per atom (DPA) damage produced by irradiations in the High Flux Isotope Reactor (HFIR) at Oak Ridge National Laboratory (ORNL) will be studied in the MPEX facility. The project presented in this paper involved performing assessments of the induced radioactivity and resulting radiation fields of a variety of potential fusion reactor materials. The scientific code packages MCNP and SCALE were used to simulate irradiation of the samples in HFIR; generation and depletion of nuclides in the material and the subsequent composition, activity levels, gamma radiation fields, and resultant dose rates as a function of cooling time. These state-of-the-art simulation methods were used in addressing the challenge of the MPEX project to minimize the radioactive inventory in the preparation of the samples for inclusion in the MPEX facility.

Ellis, Ronald James↗

Resistive switching: An investigation of the bipolar–unipolar transition in Co-doped ZnO thin films

Highlights: • A purely bipolar behavior on a Co-doped ZnO thin film has been demonstrated. • We have shown what can happen if a unipolar test is performed in a purely bipolar device. • An explanation for how a sample can show a purely bipolar switching behavior was suggested. • An important open issue about resistive switching effect was put in debate. - Abstract: In order to investigate the resistive switching effect we built devices in a planar structure in which two Al contacts were deposited on the top of the film and separated by a small gap using a shadow mask. Therefore, two samples of 10% Co-doped ZnO thin films were sputtered on glass substrate. High resolution X-ray diffraction (HRXRD) revealed a highly c-axis oriented crystalline structure, without secondary phase. The high resolution scanning electron microscopy (HRSEM) showed a flat surface with good coverage and thickness about 300 nm. A Keithley 2425 semiconductor characterization system was used to perform the resistive switching tests in the bipolar and unipolar modes. Considering only the effect of compliance current (CC), the devices showed a purely bipolar behavior since an increase in CC did not induce a transition to unipolar behavior.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Field expedient stool collection methods for gut microbiome analysis in deployed military environments

ABSTRACT Field expedient devices and protocols for the collection, storage, and shipment of stool samples in deployed settings are needed for the advancement of microbiome research in military health. Relevant assessments include the evaluation of microbiome signatures associated with susceptibility to travelers’ diarrhea and recovery of gut function following infection. However, inherent biases in microbial measurements due to preservatives and sampling methods are unclear and should be assessed for an accurate evaluation of the microbiome. We performed shotgun metagenomic sequencing and compared the microbiome composition in paired fecal samples collected using Flinters Technology Associates (FTA) cards and OMNIgene (OG) Gut tubes, prior to and during international travel, from 49 adult participants, 39 of whom remained asymptomatic and 10 experienced travelers’ diarrhea. Higher concentrations of nucleic acid and sequencing libraries were observed in OG samples. A majority of genera (82.9%) were detected with both methods, and detections of genera limited to one collection method were not highly prevalent across samples and were present in extremely low relative abundances (<0.01%). Differences in beta diversity were largely explained by inter-individuality of microbiome composition, followed by the effect of collection method and timepoint-disease states. Differential abundance analysis indicated that Corynebacterium and Blautia were consistently higher in abundance across all groups with FTA and OG collection, respectively. The observed differences in microbiome composition between methods suggest the need for consistent and standardized protocols within a study. Overall, the data presented here could help guide the future design of fecal microbiome study protocols in field and military deployment settings. IMPORTANCE The assessment of field-deployable methods for fecal sample collection and storage is required to reliably capture samples collected in remote and austere locations. This study describes a comparative metagenomics analysis between samples collected by two different commercially available methods in a military-deployed setting. The results presented here are foundational for the future design of fecal microbiome study protocols in an operational context.

field study↗

Binary frequencies in a sample of globular clusters. II. Sample analysis and comparison to models

Binary stars are predicted to have an important role in the evolution of globular clusters, so we obtained binary fractions for 35 globular clusters that were imaged in the F606W and F814W with the Advanced Camera for Surveys on the Hubble Space Telescope. When compared to the values of prior efforts, we find significant discrepancies, despite each group correcting for contamination effects and having performed the appropriate reliability tests. The most reliable binary fractions are obtained when restricting the binary fraction to q⩾0.5. Our analysis indicates that the range of the binary fractions is nearly an order of magnitude for the lowest dynamical ages, suggesting that there is a broad distribution in the binary fraction at globular cluster formation. Dynamical effects also appear to decrease the core binary fractions by a factor of two over a Hubble time, but this is a weak relationship. We confirm a correlation from previous work that the binary fraction within the core–radius decreases with cluster age, indicating that younger clusters formed with higher binary fractions. The strong radial gradient in the binary fraction with cluster radius appears to be a consequence of dynamical interactions. It is often not present in dynamically young clusters, but is nearly always present in dynamically old clusters.

79 ASTRONOMY AND ASTROPHYSICS↗

THE DIMINISHING IMPORTANCE OF MAJOR GALAXY MERGERS AT HIGHER REDSHIFTS

Using mass-selected galaxy samples from deep multiwavelength data we investigate the incidence of close galaxy pairs between z = 0.4 and 2. Many such close pairs will eventually merge, and the pair fraction is therefore related to the merger rate. Over this redshift range the mean pair fraction is essentially constant (evolving as f{sub pair} {approx} (1 + z){sup -0.4{+-}0.6}) with about 6% {+-} 1% of massive galaxies having a 1: 4 or greater companion within 30 h {sup -1} kpc. Assuming the timescale over which pairs merge is not a strong function of redshift, this implies a similarly constant merger rate (per unit time) out to z = 2. Since about three times as much cosmic time passes at z < 1 as between z = 1 and 2, this implies that correspondingly more mergers occur in the low-redshift universe. When minor companions (1:10 mass ratio or greater) are included, the pair fraction increases to {approx}20% and still does not evolve strongly with redshift. We also use a rest-frame color criterion to select pairs containing only quiescent galaxies (major 'dry merger' progenitors), and find them to be similarly rare and constant with 4%-7% of massive quiescent galaxies exhibiting a nearby companion. Thus, even though other studies find major mergers to be relatively uncommon since z = 1, our results suggest that few additional mergers occur in the 1 < z < 2 range and other mechanisms may be required to explain the mass and size growth of galaxies over this epoch.

79 ASTRONOMY AND ASTROPHYSICS↗

Sample selection and testing of separation processes

Phase partitioning, which has become an important tool for the separation and purification of biological materials, was studied. Instruments available for this technique were researched and a countercurrent distribution apparatus, the Biosheff MK2N, was purchased. Various proteins, polysaccharides and cells were studied as models to determine operating procedures and conditions for this piece of equipment. Results were compared with those obtained from other similar equipment, including a nonsynchronous coil planet centrifuge device. Additionally, work was done with affinity ligands attached to PEG, which can further enhance the separation capabilities of phase partitioning.

Karr, L. J.↗

Automated Rock Identification for Future Mars Exploration Missions

A key task for human or robotic explorers on the surface of Mars is choosing which particular rock or mineral samples should be selected for more intensive study. The usual challenges of such a task are compounded by the lack of sensory input available to a suited astronaut or the limited downlink bandwidth available to a rover. Additional challenges facing a human mission include limited surface time and the similarities in appearance of important minerals (e.g. carbonates, silicates, salts). Yet the choice of which sample to collect is critical. To address this challenge we are developing science analysis algorithms to interface with a Geologist's Field Assistant (GFA) device that will allow robotic or human remote explorers to better sense and explore their surroundings during limited surface excursions. We aim for our algorithms to interpret spectral and imaging data obtained by various sensors. The algorithms, for example, will identify key minerals, rocks, and sediments from mid-IR, Raman, and visible/near-IR spectra as well as from high resolution and microscopic images to help interpret data and to provide high-level advice to the remote explorer. A top-level system will consider multiple inputs from raw sensor data output by imagers and spectrometers (visible/near-IR, mid-IR, and Raman) as well as human opinion to identify rock and mineral samples.

Gulick, V. C.↗

Effects of finite sampling on fatigue damage estimation of wind turbine components: A statistical study

The variability of the wind turbine loads complicates fatigue assessment in the design phase, as performing simulations covering the entire lifetime is computationally expensive. The current work provides important information for assessing the uncertainty in fatigue damage estimation due to finite data. Here we study the sample size effect on mean, variance, and skewness of damage in each wind bin, identify the important wind bins, and study the uncertainty propagation from each wind bin to the lifetime damage using 3600 aeroelastic simulations and bootstrapping. To achieve less than 1% error in the damage estimation across all load channels in the current case study, at least 100 turbulence seeds are needed. Damage in different wind bins follows a lognormal distribution when using the conventional approach of six seeds. The provided insights and information allow the designer to achieve a specific level of accuracy for a given computational cost using strategic bin sampling.

17 WIND ENERGY↗

Climatic Controls on Residual Contaminants Under Sustainable Remediation - 18699

We investigate the impact of climate change on residual contaminants in soil and groundwater under sustainable remediation. We illustrate seven climate change scenarios which mimic shifts in the precipitation regime as well as the failure of the source-zone cap. We evaluate different performance metrics including contaminant concentrations at multiple wells and export to a creek. The approach is demonstrated by simulating the tritium plume migration at the Savannah River Site F-Area, USA. The cap integrity is critical not only to reduce the well concentrations and export but also to reduce the uncertainty associated with the climatic variability. Sampling or in situ monitoring near the source zone is important for the early detection of plume mobility changes. Realistic hydrological models are necessary to evaluate the trade-offs (mobility vs dilution)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Delayed-Gamma Energy Biasing with Exact Energy Sampling in MCNP 6.2.0

Characterization of delayed-particle signatures is of the utmost importance for detecting, identifying, and quantifying special nuclear material (SNM). Various non-destructive assay (NDA) techniques used in nuclear material safeguards rely on characteristic gamma-ray or neutron emissions to infer properties of a material. The all-particle, all-energy Monte-Carlo radiation transport code MCNP6 is capable of simulating delayed-particle signatures from SNM in addition to modeling the transport of emitted particles to a detector or other instrument. In some cases, NDA techniques require the measurement of low probability emissions from a given material. In physical scenarios, this problem can be bypassed by longer count-times or may be simply irrelevant due to the mass, and therefore the total activity, of the material being measured. However, when applying the Monte-Carlo method to such scenarios, sampling of low probability emissions requires a large number of histories to converge to a statistically acceptable solution. To address this issue, the delayed-neutron and gamma energy biasing feature was introduced in MCNP6 by H. Armstrong et al. in 2013 which allows the user to set up energy windows in which delayed-particle emission sampling can be adjusted. For delayed-gamma sampling, this biasing method was based on the bin-wise structure of gamma emission data for both the multi-bin gamma and line-emission sampling modes. Recent improvements have been made to the line-emission sampling algorithm which upgrade the previous mini-bin sampling treatment to an exact energy-line treatment. This upgrade was not compatible with the biasing method implemented by H. Armstrong et al. due to the sampled data no longer having a bin-wise structure in line-emission mode. For this reason the delayed-gamma energy biasing feature has been rewritten to support the exact line-sampling treatment. This paper provides a description of the delayed-gamma energy biasing (DGEB) feature in MCNP6 as well as results and discussion for a gamma-ray spectroscopy example used to demonstrate the biasing utility. (authors)

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Illustrating galaxy–halo connection in the DESI era with illustrisTNG

ABSTRACT We employ the hydrodynamical simulation illustrisTNG to inform the galaxy–halo connection of the Luminous Red Galaxy (LRG) and Emission Line Galaxy (ELG) samples of the Dark Energy Spectroscopic Instrument (DESI) survey at redshift z ∼ 0.8. Specifically, we model the galaxy colours of illustrisTNG and apply sliding DESI colour–magnitude cuts, matching the DESI target densities. We study the halo occupation distribution (HOD) model of the selected samples by matching them to their corresponding dark matter haloes in the illustrisTNG dark matter run. We find the HOD of both the LRG and ELG samples to be consistent with their respective baseline models, but also we find important deviations from common assumptions about the satellite distribution, velocity bias, and galaxy secondary biases. We identify strong evidence for concentration-based and environment-based occupational variance in both samples, an effect known as ‘galaxy assembly bias’. The central and satellite galaxies have distinct dependencies on secondary halo properties, showing that centrals and satellites have distinct evolutionary trajectories and should be modelled separately. These results serve to inform the necessary complexities in modelling galaxy–halo connection for DESI analyses and also prepare for building high-fidelity mock galaxies. Finally, we present a shuffling-based clustering analysis that reveals a 10–15 ${{\ \rm per\ cent}}$ excess in the LRG clustering of modest statistical significance due to secondary galaxy biases. We also find a similar excess signature for the ELGs, but with much lower statistical significance. When a larger hydrodynamical simulation volume becomes available, we expect our analysis pipeline to pinpoint the exact sources of such excess clustering signatures.

79 ASTRONOMY AND ASTROPHYSICS↗