Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “sampling variability”

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 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Sensitivity ZAM Modeling Study of Tank 10H VDS Waste Sample (U)

The objective of this work is to study the sensitivity of cesium loading expected on the Tank Closure Cesium Removal (TCCR) columns. Savannah River National Laboratory (SRNL) utilized ZAM, a computer program developed by the research group of Professor Rayford G. Anthony of Texas A&M University, for prediction of cesium loading on the Crystalline Silicotitanate (CST) resin during the processing of Tank 10H Variable Depth Sample (VDS) waste solution.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2017

Typical aqueous rare earth element behavior in co-produced Brines, Wyoming

Normalization of Rare Earth Elements (REEs) is important to remove the distracting effects of the Oddo–Harkins rule and provide a meaningful baseline. Normalizations for rocks are well developed and include chondritic meteorites, UCC, PM, PAAS, and NASC. However normalizations for aqueous REEs are limited to oceanic regions such as the North Pacific Deep Water or North Atlantic Surface Water. This leaves water in contact with continental lithologies without a suitable normalization. We present a preliminary continental aqueous REE normalization derived from 38 deep basin hydrocarbon brines in Wyoming. The REEs in these waters are seven orders of magnitude more dilute than NASC but with significant europium enrichment. Gromet 1984 reports NASC Eu/Eu* is 0.2179, whereas in the normalization offered here, Eu/Eu* is 3.868. These waters also are free from the distracting reduction-oxidation cerium behavior found in ocean normalizations. Because these samples exhibit both the uniform behavior of NASC and the absolute concentration of seawater, a normalization based upon them offers a unique combination of the advantages of both. We used single-peak gaussian analysis to quantify the mean values for each REE and estimate the distribution variability. Additional sample collection during the last year revealed that the Powder River Basin (PRB) is atypical relative to the other sampled basins of Wyoming. Those other basins are the Wind River Basin (WRB) Green River Basin (GRB) and Wamsutter Area (WA). A pre-normalization gadolinium anomaly (Gd/Gd*) of between 4 and 23 with a mean of 11.5, defines the PRB samples. Other basins in this study range from 1 to 7 with a mean of 2.8. Finally, we present a preliminary model for ligand-based behavior of REEs in these samples. This model identifies bicarbonate, bromide, and chloride as forming significant complexes with REEs contributing to REE solubility. The ligand model explains observed REEs in the sampled Cretaceous and Paleocene clastic reservoirs. However, the presence of more REEs than predicted in six samples suggests that there is an additional, unconsidered ligand contributing to REE dissolution. Further work will identify this ligand, which appears to be confined to calcium-cemented and dolostone systems.

02 PETROLEUM↗
DOE OSTI2022

Spatially resolved properties of early-type group-dominant galaxies with MUSE: gas content, ionization mechanisms, and metallicity gradients

ABSTRACT With the goal of a thorough investigation of the ionized gas and its origin in early-type group-dominant galaxies, we present archival MUSE data for 18 galaxies from the Complete Local-Volume Groups Sample (CLoGS). These data allowed us to study the spatially resolved warm gas properties, including the morphology of the ionized gas, EW(H α), and kinematics as well as the gas-phase metallicity (12 + log(O/H)) of these systems. In order to distinguish between different ionization mechanisms, we used the emission-line ratios [O iii]/H β and [N ii]/H α in the BPT diagrams and EW(H α). We find that the ionization sources in our sample have variable impacts at different radii; central regions are more influenced by low-luminosity active galactic nuclei, while extended regions of low-ionization nuclear emission-line region-like emission are ionized by other mechanisms with post-asymptotic giant branch stars photoionization likely contributing significantly. We classified our sample into three H α +[N ii] emission morphology types. We calculate the gas-phase metallicity assuming several methods and ionization sources. In general, 12 + log(O/H) decreases with radius from the centre for all galaxies, independently of nebular morphology type, indicating a metallicity gradient in the abundance profiles. Interestingly, the more extended filamentary structures and all extranuclear star-forming regions present shallow metallicity gradients. Within the uncertainties these extended structures can be considered chemically homogeneous. We suggest that group-dominant galaxies in our sample likely acquired their cold gas in the past as a consequence of one or more mechanisms, e.g. gas-clouds or satellite mergers/accretion and/or cooling flows that contribute to the growth of the ionized gas structures.

Lagos, P. (ORCID:0000000223218657)↗
NASA NTRS2014

Reply to Comment by Laprise on 'the Added Value to Global Model Projections of Climate Change by Dynamical Downscaling: a Case Study over the Continental U.S. Using the GISS-ModelE2 and WRF Models'

In his comment, Laprise raises several points that we agree merit consideration. His primary critique is that our study [Racherla et al., 2012] tested the ability of the WRF regional climate model to reproduce historical temperature and precipitation change relative to the driving global climate model (GCM) using only a single simulation rather than an ensemble. He asserts that the observed changes are smaller than the internal variability in the climate system (i.e., not statistically significant) and that thus a single simulation should not necessarily be able to capture the observations. Laprise points out that the statistical signal is reduced for a multi-decadal trend such as the one we analyzed in comparison with mean climatology and cites two studies showing that for particular climate parameters it can take any years for a signal to be discerned over internal variability. He states that The results of theexperiment as designed were strongly influenced by the presence of internal variability and sampling errors,which masked the rather small climate changes that may have occurred as a consequence of changes inforcing during the period considered. While Laprise discusses statistics in general terms at some length, for the actual climate trends examined in our study, he offers no evidence that the forced signal was smallcompared with internal variability. The two studies he cites [de Ela et al., 2013; Maraun, 2013] do not provide convincing evidence as they concern climate variables averaged over different times and areas. One in fact examines extreme precipitation events, which by definition are rare and thus have a lower significance level. We accept the general point that it is important to consider internal variability, and as noted in our paper we agree that an ensemble of simulations is in principle an optimal, though computationally expensive, approach. While we did not present the statistical significance of the observations in our original paper, we have now evaluated those for the regional temperature trends used in our study to evaluate the added value of WRF and thus can analyze data as to the magnitude of the trends with respect to internal variability.

climate↗
DOE OSTI2017

On the Origin of Sub-subgiant Stars. I. Demographics

Sub-subgiants are stars that are observed to be redder than normal main-sequence stars and fainter than normal subgiant (and giant) stars in an optical color–magnitude diagram (CMD). The red straggler stars, which lie redward of the red giant branch, may be related and are often grouped together with the sub-subgiants in the literature. These stars defy our standard theory of single-star evolution and are important tests for binary evolution and stellar collision models. In total, we identify 65 sub-subgiants (SSG) and red stragglers (RS) in 16 open and globular star clusters from the literature; 50 of these, including 43 sub-subgiants, pass our strict membership selection criteria (though the remaining sources may also be cluster members). In addition to their unique location on the CMD, we find that at least 58% (25/43) of sub-subgiants in this sample are X-ray sources with typical 0.5–2.5 keV luminosities of order 10{sup 30}–10{sup 31} erg s{sup −1}. Their X-ray luminosities and optical–to–X-ray flux ratios are similar to those of RS CVn active binaries. At least 65% (28/43) of the sub-subgiants in our sample are variables, 21 of which are known to be radial-velocity binaries. Typical variability periods are ≲15 days. At least 33% (14/43) of the sub-subgiants are H α emitters. These observational demographics provide strong evidence that binarity is important for sub-subgiant formation. Finally, we find that the number of sub-subgiants per unit mass increases toward lower-mass clusters, such that the open clusters in our sample have the highest specific frequencies of sub-subgiants.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2018

Equilibration and analysis of first-principles molecular dynamics simulations of water

First-principles molecular dynamics (FPMD) simulations based on density functional theory are becoming increasingly popular for the description of liquids. In view of the high computational cost of these simulations, the choice of an appropriate equilibration protocol is critical. In this study, we assess two methods of estimation of equilibration times using a large dataset of first-principles molecular dynamics simulations of water. The Gelman-Rubin potential scale reduction factor [A. Gelman and D. B. Rubin, Stat. Sci. 7, 457 (1992)] and the marginal standard error rule heuristic proposed by White [Simulation 69, 323 (1997)] are evaluated on a set of 32 independent 64-molecule simulations of 58 ps each, amounting to a combined cumulative time of 1.85 ns. The availability of multiple independent simulations also allows for an estimation of the variance of averaged quantities, both within MD runs and between runs. We analyze atomic trajectories, focusing on correlations of the Kohn-Sham energy, pair correlation functions, number of hydrogen bonds, and diffusion coefficient. The observed variability across samples provides a measure of the uncertainty associated with these quantities, thus facilitating meaningful comparisons of different approximations used in the simulations. We find that the computed diffusion coefficient and average number of hydrogen bonds are affected by a significant uncertainty in spite of the large size of the dataset used. Lastly, a comparison with classical simulations using the TIP4P/2005 model confirms that the variability of the diffusivity is also observed after long equilibration times. Complete atomic trajectories and simulation output files are available online for further analysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1981

Adsorption of xenon and krypton on shales

A method that uses a mass spectrometer as a manometer is employed in the measurement of Xe and Kr adsorption parameters on shales and related samples, where gas partial pressures were lower than 10 to the -11th atm, corresponding adsorption coverages are only small fractions of a monolayer, and Henry's Law behavior is expected and observed. Results show heats of adsorption in the 2-7 kcal/mol range, and Henry constants at 0-25 C of 1 cu cm STP/g per atmosphere are extrapolated. Although the adsorption properties obtained are variable by sample, the range obtained suggests that shales may be capable of an equilibrium adsorption with modern air high enough to account for a significant fraction of the atmospheric inventory of Xe, and perhaps even of Kr. This effect will nevertheless not account for the factor-of-25 defficiency of atmospheric Xe, in comparison with the planetary gas patterns observed in meteorites.

Podosek, F. A.↗
DOE OSTI2026

Statistical Uncertainty of Inhalation Dose Coefficients in Consequence Management: Propagated Dose Uncertainty in ICRP 66 Human Respiratory Tract Model

Reference inhalation dose models rely on deterministic biokinetics and reference computational phantoms, limiting their applicability to the variability present in population-specific exposures encountered in emergency response scenarios. Here, this study introduces REDCAL, a Python-based computational framework developed to propagate uncertainty in inhalation dose coefficients using the International Commission on Radiological Protection (ICRP) Publication 66 Human Respiratory Tract Model. REDCAL integrates ICRP deposition and clearance models, systemic biokinetics, and governing physics principles, and leverages Sandia National Laboratories’ Dakota toolkit for uncertainty quantification via Latin Hypercube Sampling. REDCAL was validated against DCAL, with biokinetic retention results differing by less than 1% and effective dose coefficients by less than 2% across all tested radionuclides. Stochastic sampling introduced variability in dose coefficients, with geometric standard deviations (GSD) in committed effective dose coefficients (CEDC) ranging from 1.0 to 1.5, based on lognormal distribution fits. Analysis demonstrated that variations in the activity median aerodynamic diameter (AMAD) notably influenced the computed CEDC values. Smaller particles (<1 µm) increased doses by 20–30% due to deeper lung deposition and prolonged retention for alpha emitting radionuclides, such as 241 Am and 239 Pu. Radionuclides with fast clearance, such as 133 I, demonstrated a dose reduction exceeding 50%, as AMAD increased beyond 5 µm due to upper airway deposition and rapid mucociliary clearance. The greatest GSD among the radionuclides reported in this study was for 241 Am. In most cases, the largest GSDs in the CEDC were associated with larger particle sizes, an expected outcome, as ICRP Publication 66 defines GSD in particle size as a function of AMAD, resulting in an extended tail of the lognormal distribution. The findings support improved inhalation dose assessments and enhance consequence management strategies for the U.S. Federal Radiological Monitoring and Assessment Center by quantifying uncertainty in dose coefficients and strengthening decision-making for emergency response scenarios.

Biokinetic Modeling↗
DOE OSTI2020

Comparison of four learning-based methods for predicting groundwater redox status

Knowing the location where groundwater denitrification occurs, or by proxy the groundwater redox status (oxic, mixed, and anoxic), is valuable information for assessing and managing potential agricultural land-use impacts on freshwater quality. We compare the efficacy of supervised (Linear Discriminant Analysis LDA; Boosted Regression Trees, BRT; and Random Forest, RF) and unsupervised (Modified Self-Organizing Map, MSOM) learning-based methods to predict groundwater redox status in the agriculturally dominated Tasman, Waikato, and Wellington regions of New Zealand. Thresholds applied to regional groundwater-quality samples provide redox status variables and learn heuristics constrained by these variables and applied to spatial factors (climate, elevation, geologic, hydrology soils, and well depth) identify optimal sets of regional predictor variables. A split-sample approach is used to train and test the learning methods ability to predict redox status using the optimal predictor variables. Overall, the supervised methods demonstrate a prediction bias toward oxic conditions and inability to perform statistically well when using independent regional data; for example, consider kappa statistics for BRT (Tasman: 0.42, Waikato: 0.38, Wellington: 0.17), RF (Tasman: 0.42, Waikato: 0.47, Wellington: 0.17 and LDA (Tasman: 0.46, Waikato: 0.32, Wellington: 0.17). By contrast, the unsupervised method performs statistically well when predicting oxic, mixed, and anoxic conditions and corresponding depths when using independent regional data; for example, consider MSOM kappa statistics for Tasman: 0.78, Waikato: 0.80, Wellington: 0.76. The unsupervised learning method provides the added benefits of being (1) able to combine predictions into 3D regional anoxic probability plots for interpreting the spatial influence of paleosols and groundwater flowpaths on redox status, and (2) readily extended to map 3D redox status across New Zealand and other countries despite data bias and sparsity.

machine learning algorithms, Random Forest, booste↗
DOE OSTI2021

Co-expression networks in Chlamydomonas reveal significant rhythmicity in batch cultures and empower gene function discovery

The unicellular green alga Chlamydomonas reinhardtii is a choice reference system for the study of photosynthesis and chloroplast metabolism, cilium assembly and function, lipid and starch metabolism, and metal homeostasis. Despite decades of research, the functions of thousands of genes remain largely unknown, and new approaches are needed to categorically assign genes to cellular pathways. Growing collections of transcriptome and proteome data now allow a systematic approach based on integrative co-expression analysis. We used a dataset comprising 518 deep transcriptome samples derived from 58 independent experiments to identify potential co-expression relationships between genes. We visualized co-expression potential with the R package corrplot, to easily assess co-expression and anti-correlation between genes. We extracted several hundred high-confidence genes at the intersection of multiple curated lists involved in cilia, cell division, and photosynthesis, illustrating the power of our method. Surprisingly, Chlamydomonas experiments retained a significant rhythmic component across the transcriptome, suggesting an underappreciated variable during sample collection, even in samples collected in constant light. Our results therefore document substantial residual synchronization in batch cultures, contrary to assumptions of asynchrony. We provide step-by-step protocols for the analysis of co-expression across transcriptome data sets from Chlamydomonas and other species to help foster gene function discovery.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Towards resolving protein structures at the atomic scale using atom probe tomography

In the field of Structural Biology, Atom Probe Tomography (APT) is in the nascent stages of development wherein coarse-grained visuals of proteins have been captured. The characterization of organic samples or biomolecules through the technique is currently limited to the detection of a few dominant signatures. The problem of indecipherable characterization can inherently be traced back to multiple forms of technique-specific responses to organic samples and consequent triggers leading to organic-sample and sample-medium interactions. While it is possible for captured manifestations of protein reconstructions to seemingly appear intact from a basic visual purview, the parameter-protein associative responses throughout the structure as a direct consequence of the inherent workings of the technique (until harmonized with organic sample complexity and behavior) and field evaporation-based factors make non-aberrative atomic associations infeasible. The work focused on identifying and theorizing the (above stated and other) fundamental mechanisms that stronghold the study of intricate atomic to higher order associations in proteins through APT. Attempts at structure elucidation of the cryogenic sample under study, through indirect associations (and methods) based on other imaging techniques, further revealed the distinct and highly distortive nature at the atomic scale deterring structural tunability and thus characterization of APT based cryogenic samples under analysis. As a direct counter to the atomic scale characterization problem, by taking the experiment-specific uncertainties, and probable APT-centric organic sample-based variabilities into account, a basic result is extracted and presented. Through mass-spectrometric and computational analysis, specific individual amino acids (Sulfur-containing protein-bound amino acids) in proteins and aspects of protein structure (probable backbone fragments, partial sequence - partial backbone portions) have been identified and characterized. Under analysis considerations, a few of the simplest known and easily inferable segments that favor structural deteriorations in the reconstructions are stated. Additionally, to overcome technique-specific deterrents to the characterization of biomolecules in cryogenic sample medium, the development of a protein-labeling strategy tailored to APT is suggested.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Characterization of Tank 11H samples from tank closure cesium removal (TCCR) Batch 3 - intermediate and final samples

Savannah River Remediation (SRR) is currently operating the Tank Closure Cesium Removal (TCCR) process to remove 137 Cs from tank waste supernate using an ion exchange process. The TCCR unit processes dissolved salt from Tank 10H through a series of ion exchange columns containing crystalline silicotitanate (CST) and the effluent is then discharged to Tank 11H. Four interim samples pulled from Tank 11H during and just after the completion of processing of Batch 3 through the TCCR process have been analyzed for 137 Cs activity and density. The 137 Cs activity was found to decrease with each subsequent sample, which is consistent with the addition of decontaminated solution to Tank 11H. When compared to the expected composition from mixing the Tank 10H Batch 3 feed with the material already present in Tank 11H, the bulk chemical composition was as expected. A corrosion control sample collected from Tank 11H in June 2020 showed changes in the chemical composition and 137 Cs activity when compared to the composition measured at the end of Batch 2 processing. As there were no additions made to the tank during this period, these changes were attributed to leaching of the solids present in Tank 11H. Revision 1 of this report contains additional analyses of the fourth interim sample including inductively coupled plasma – mass spectrometry (ICP-MS) results and activities of other radionuclides. These results are consistent with the previously reported results, showing leaching from the Tank 11H heel. Notably, the 90 Sr activity was about 2.7x higher than calculated from a mixture of the original Tank 11H supernate and the Tank 10H supernate as treated by TCCR, suggesting additional leaching of Sr from the Tank 11H heel solids. In addition, Revision 1 includes analysis results for the Batch 3 Post-Production surface and variable depth samples collected in October of 2020. The Post-Production surface sample was similar in composition to the fourth interim surface sample, except for the increased Cs-137 and oxalate concentrations that were presumably associated with leaching of the Tank 11H heel solids.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2026

Typha angustifolia non-destructive biomass data from an upland tidal brackish marsh, PIE LTER, Byfield, MA, (2022-2024)

This dataset contains non-destructive measurements of key features of Typha angustifolia samples. These samples were measured during the growing season in 2022, 2023, and 2024 in an upland brackish tidal wetland along the Parker River, Byfield, Massachusetts (MA), which is within the Plum Island Ecosystems Long Term Ecological Research Station (PIE LTER). Measurements were taken to investigate the difference in above ground biomass between two locations, the marsh interior (MI) and the creek bank (CB) and to support an allometric equation used to predict aboveground Typha angustifolia biomass per square meter. No QA/QC procedures were applied to the data. Metadata files Typha_biomass_observations_dd.csv and Typha_biomass_observations_flmd.csv contain detailed information on variable definitions, sampling methods, and the location of the site.

CULM_D_1↗
DOE OSTI2019

Passively Sampled Environmental Films Show Geographic Variability and Host a Variety of Microorganisms

Environmental films are ubiquitous coatings that form on virtually all surfaces exposed to the troposphere. This work analyzes large molecular weight species in native environmental films acquired at three collection sites in the vicinity of Iowa City, Iowa, USA that include an urban residence, a wooded area, and a metropolitan building rooftop. The films are developed for up to twelve months on polished silicon wafer substrates housed in flat-plate passive samplers. Film composition was assessed by Fourier transform ion cyclotron resonance secondary ion mass spectrometry (FTICR-SIMS), and spatially resolved chemical morphology was analyzed via timeof- flight secondary ion mass spectrometry (ToF-SIMS) imaging. Mass analysis spanning up to m/z 2,000 included detection of a variety of organic and inorganic compounds. We characterize MS data with PCA to identify variability between the collection sites and the respective films generated therein, where we detected a variety of organic and biotically generated species consistent with fungal and bacterial microorganisms. Here, the film collection site as well as deposition time contribute to spectral variability, suggesting that geographic location as well as seasonal diversity may affect composition. SIMS analyses were complemented with microscopy and SYBR-Safe staining to highlight biological microorganisms within the films, which include evidence of fungi, protozoa, and bacteria. SIMS imaging also reveals domains concentrated with fragments indicative of proteinaceous macromolecules and microbial biomass, characteristic of biological presence within the film.

42 ENGINEERING↗
DOE OSTI2020

Thermal transport across nanoscale damage profile in sapphire irradiated by swift heavy ions

In this work, we studied the degradation of thermal conductivity in single crystal sapphire (α-Al 2 O 3 ) irradiated by 167 MeV Xe swift heavy ions (SHIs) over the multiple fluences in the range of 10 12 –10 14 ions/cm 2 . Thermal conductivity was measured primarily in the cross-plane direction using a noncontact ultrafast optical pump-probe technique called picosecond time domain thermoreflectance (TDTR). Multiple samples with variable ion fluences allowed us to probe distinct regions resulting from different regimes of microstructure evolution caused by electronic energy loss. By tuning the penetration depth of the thermal waves using different modulation frequencies, two regions with distinct conductivities were identified and the values of which were found to be consistent with phonon-mediated thermal transport models while the microstructure was confirmed by electron microscopy characterization. These damaged regions were determined to be a several micrometer thick ion track region and several tens of nanometer-thick amorphous layer present only above 5.0 × 10 13 ions/cm 2 . These results demonstrate the applicability of TDTR to resolve thermal transport behavior in SHI irradiated oxides having nonhomogeneous damage profile on a nanometer scale. The presented approach facilitates future studies aiming at resolving the impact of distinct damage resulting from electronic and nuclear stopping regimes under irradiation.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

In situ saxs characterization of thermoresponsive behavior of a poly(ethylene glycol)-graft-(poly(vinyl caprolactam)-co-poly(vinyl acetate)) amphiphilic graft copolymer

In this work, we report the thermoresponsive assembly and rheology of an amphiphilic thermosensitive graft copolymer, poly(ethylene glycol)-graft-(poly(vinyl caprolactam)-co-poly(vinyl acetate)) (commercial name Soluplus ® ), which has been investigated for potential biomedical applications. It has received attention due to is ability to solubilize hydrophobic drugs and for its thickening behavior close to body temperature. Through use of the synchrotron at Brookhaven National Lab, and collaboration with the department of energy, the nanoscale structure and properties can be probed in greater detail. Soluplus ® undergoes two structural changes as temperature is increased; the first, a concentration independent change where samples become turbid at 32 °C. Increasing the temperature further causes the formation of physically associated hydrogels. This sol-gel transition is concentration dependent and occurs at 32 °C for 40 wt% samples, and increases to 42 °C for 10 wt% samples. From variable temperature SAXS characterization micelles of 20–25 nm in radius can be seen and maintain their size and packing below 32 °C. A gradual increase in the aggregation of micelles corresponding to a thickening of the material is also observed. Close to and above the gelation temperature, micelles collapse and form a physically associated 3D network. A model is proposed to explain these physical effects, where the poly(vinyl caprolactam) group transitions from the hydrophilic corona at room temperature to the hydrophobic core as temperature is increased.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Phase-resolved terahertz nanoimaging of W Te 2 microcrystals

The terahertz (THz) electrodynamics of few-layer W⁢Te 2 is dominated by the plasmon response. However, THz surface plasmons (SPs) with long wavelengths in two-dimensional exfoliated crystals are typically confined by the lateral geometry. Direct visualization of the plasmonic standing wave patterns is challenging due to the spatial confinement and low quality factor of the SP, especially for samples that are only a few monolayers thick. Here, we resolve subtle real-space features of the plasmonic response of W⁢Te 2 by augmenting more common scattering amplitude experiments with the phase contrast accomplished within the time-domain version of THz nanoimaging. Amplitude and phase images allow us to quantitatively evaluate the evolution of the plasmonic response at cryogenic temperatures in samples with variable thickness from 3 to 12 monolayers. Further, the proposed imaging modality is universally applicable to the THz near-field nanoscopy of low-dimensional materials.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

Probabilistic neural networks for fluid flow surrogate modeling and data recovery

We consider the use of probabilistic neural networks for fluid flow surrogate modeling and data recovery. This framework is constructed by assuming that the target variables are sampled from a Gaussian distribution conditioned on the inputs. Consequently, the overall formulation sets up a procedure to predict the hyperparameters of this distribution which are then used to compute an objective function given training data. We demonstrate that this framework has the ability to provide for prediction confidence intervals based on the assumption of a probabilistic posterior, given an appropriate model architecture and adequate training data. The applicability of the present framework to cases with noisy measurements and limited observations is also assessed. To demonstrate the capabilities of this framework, we consider canonical regression problems of fluid dynamics from the viewpoint of reduced-order modeling and spatial data recovery for four canonical data sets. The examples considered in this study arise from (i) the shallow-water equations, (ii) a two-dimensional cylinder flow, (iii) the wake of a NACA0012 airfoil with a Gurney flap, and (iv) the NOAA sea surface temperature data set. Furthermore, the present results indicate that the probabilistic neural network not only produces a machine-learning-based fluid flow surrogate model but also systematically quantifies the uncertainty therein to assist with model interpretability.

42 ENGINEERING↗