SEARCH · Engineering Papers

Results for “Surface estimation”

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.

SourceResearch connectionFrom yearThrough year

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

At least 1,045 records · Page 58

All sources NASA NTRS DOE OSTI

DOE OSTI2021

Adapting confocal Raman microscopy for in situ studies of redox transformations at electrode-electrolyte interfaces

Confocal Raman microscopy was applied to quantify redox species present within the diffusion layer adjacent to an electrode surface under potentiostatic control. A glass microscope coverslip with a thin indium tin oxide (ITO) coating served as both the working electrode and optical window for a microscope-stage mountable spectroelectrochemical cell. A high numerical aperture objective mounted in an inverted microscope frame just below the stage brought excitation radiation through the coverslip window and to a tight focus a few micrometers above the ITO film surface. Species diffusing into the confocal probe volume defined by the excitation beam focus and the collected light region were detected, identified and quantified based on their Raman scattering frequencies and intensities. Here, in measurements that interrogated the interconversion of ferrocyanide and ferricyanide ions as a function of applied voltage, least-squares regression analysis of spectral datasets predicted the formal potential and relative surface concentrations of the ions in good agreement with the expected Nernstian response. Preliminary studies of methyl viologen reduction at an ITO film/Nafion membrane interface were conducted and show the possibility for estimation of mass transport coefficients of redox species within ionic polymer materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

X-ray imaging of liquid-liquid Mg cavitation

The coupling of dynamic loading platforms with synchrotron light sources have enabled experiments examining void formation in optically opaque materials. Much like spallation in a solid, cavitation occurs when rarefaction waves collide within a liquid. The resulting deformation leads to a complex flow field with numerous voids. It has been suggested that compaction of such a structure may be a significant source of ejecta (i.e. shallow bubble collapse). Experiments imaging supported and unsupported shocks interacting with a free surface in shock melted Mg with synchrotron radiation are presented. Here, the results are used to examine the structure of a cavitation plane that forms in the unsupported case and provide an estimate of the porosity within this region.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2023

Bayesian Parameter Estimation of the k-ω Shear Stress Transport Model for Accurate Simulations of Impinging-Jet Heat Transfer

Given the lack of fusion-relevant component test facilities, current estimates of the thermo-fluid performance of plasma-facing components are based for the most part on numerical simulations. A major source of uncertainty in these simulations is the semiempirical turbulence (closure) models for the Reynolds stresses appearing in the governing Reynolds-averaged Navier-Stokes equations, which involve a set of constants that depend upon the flow. The objective of this study is to evaluate Bayesian parameter estimation of turbulence closure constants in ANSYS Fluent to model heat transfer in impinging jets. The Bayesian statistical calibration produces a probability distribution for these constants from experimental data; the maximum a posteriori estimates are then taken to be the calibrated constants, or parameters. The turbulence model constants are calibrated using an experimental study of a submerged jet of air impinging on a flat heated surface at Reynolds numbers Re = O(10 4 ) and impingement distance in jet diameters H/d = 2. Numerical predictions using the calibrated model parameters are then compared with those generated using the default constants. Predictions obtained with model parameters calibrated on datasets of two different sizes are compared to evaluate the effect of the number of calibration samples. Lastly, the extrapolative ability of the calibrated model is examined by predictions at a Re beyond the calibration values.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2025

Observation of a new isomer in {sup 185}Au

Delayed γ-ray spectroscopy of 185Au was studied at the Argonne Gas-Filled Analyzer. A new isomer at an excitation energy of 1504.2(4) keV with a half-life of 630(80) ns was identified via γ-γ coincidence analysis, decaying via a 294.8(3) keV transition. Based on Weisskopf estimates, the multipolarity of the 295 keV transition is assigned to be E1, M1, E2, or M2. Possible configurations for this new isomer are discussed based on configuration-constrained potential energy surface calculations.

Fu, X. Y.↗

DOE OSTI2025

Probing the PeV region in the astrophysical neutrino spectrum using 𝜈 𝜇 from the Southern sky

IceCube has observed a diffuse astrophysical neutrino flux over the energy region from a few TeV to a few PeV. At PeV energies, the spectral shape is not yet well measured due to the low statistics of the data. This analysis probes the gap between 1 and 10 PeV by using high-energy downgoing muon neutrinos. Here, to reject the large atmospheric muon background, two complementary techniques are combined. The first technique selects events with high stochasticity to reject atmospheric muon bundles whose stochastic energy losses are smoothed due to high muon multiplicity. The second technique vetoes atmospheric muons with the IceTop surface array. Using 9 yrs of data, we found two neutrino candidate events in the signal region, consistent with expectation from background, each with relatively high signal probabilities. A joint maximum likelihood estimation is performed using this sample and an independent 9.5-yr sample of tracks to measure the neutrino spectrum. A likelihood ratio test is done to compare the single power-law (SPL) vs SPL+cutoff hypothesis; the SPL+cutoff model is not significantly better than the SPL. High-energy astrophysical objects from four source catalogs are also checked around the direction of the two events. No significant coincidence was found.

Abbasi, R. [Loyola University Chicago] (ORCID:0000↗

DOE OSTI2023

Insights into the vulnerability of Antarctic glaciers from the ISMIP6 ice sheet model ensemble and associated uncertainty

Abstract. The Antarctic Ice Sheet represents the largest source of uncertainty in future sea level rise projections, with a contribution to sea level by 2100 ranging from −5 to 43 cm of sea level equivalent under high carbon emission scenarios estimated by the recent Ice Sheet Model Intercomparison for CMIP6 (ISMIP6). ISMIP6 highlighted the different behaviors of the East and West Antarctic ice sheets, as well as the possible role of increased surface mass balance in offsetting the dynamic ice loss in response to changing oceanic conditions in ice shelf cavities. However, the detailed contribution of individual glaciers, as well as the partitioning of uncertainty associated with this ensemble, have not yet been investigated. Here, we analyze the ISMIP6 results for high carbon emission scenarios, focusing on key glaciers around the Antarctic Ice Sheet, and we quantify their projected dynamic mass loss, defined here as mass loss through increased ice discharge into the ocean in response to changing oceanic conditions. We highlight glaciers contributing the most to sea level rise, as well as their vulnerability to changes in oceanic conditions. We then investigate the different sources of uncertainty and their relative role in projections, for the entire continent and for key individual glaciers. We show that, in addition to Thwaites and Pine Island glaciers in West Antarctica, Totten and Moscow University glaciers in East Antarctica present comparable future dynamic mass loss and high sensitivity to ice shelf basal melt. The overall uncertainty in additional dynamic mass loss in response to changing oceanic conditions, compared to a scenario with constant oceanic conditions, is dominated by the choice of ice sheet model, accounting for 52 % of the total uncertainty of the Antarctic dynamic mass loss in 2100. Its relative role for the most dynamic glaciers varies between 14 % for MacAyeal and Whillans ice streams and 56 % for Pine Island Glacier at the end of the century. The uncertainty associated with the choice of climate model increases over time and reaches 13 % of the uncertainty by 2100 for the Antarctic Ice Sheet but varies between 4 % for Thwaites Glacier and 53 % for Whillans Ice Stream. The uncertainty associated with the ice–climate interaction, which captures different treatments of oceanic forcings such as the choice of melt parameterization, its calibration, and simulated ice shelf geometries, accounts for 22 % of the uncertainty at the ice sheet scale but reaches 36 % and 39 % for Institute Ice Stream and Thwaites Glacier, respectively, by 2100. Overall, this study helps inform future research by highlighting the sectors of the ice sheet most vulnerable to oceanic warming over the 21st century and by quantifying the main sources of uncertainty.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

A structural analysis of ordered Cs3Sb films grown on single crystal graphene and silicon carbide substrates

Alkali antimonides are well established as high efficiency, low intrinsic emittance photocathodes for accelerators and photon detectors. However, conventionally grown alkali antimonide films are polycrystalline with surface disorder and roughness that can limit achievable beam brightness. Ordering the crystalline structure of alkali antimonides has the potential to deliver higher brightness electron beams by reducing surface disorder and enabling the engineering of material properties at the level of atomic layers. In this report, we demonstrate the growth of ordered Cs3Sb films on single crystal substrates 3C-SiC and graphene-coated 4H-SiC using pulsed laser deposition and conventional thermal evaporation growth techniques. The crystalline structures of the Cs3Sb films were examined using reflection high energy electron diffraction and x-ray diffraction diagnostics, while film thickness and roughness estimates were made using x-ray reflectivity. With these tools, we observed ordered domains in less than 10 nm thick films with quantum efficiencies greater than 1% at 530 nm. Moreover, we identify structural features such as Laue oscillations indicative of highly ordered films. We found that Cs3Sb films grew with flat, fiber-textured surfaces on 3C-SiC and with multiple ordered domains and sub-nanometer surface roughness on graphene-coated 4H-SiC under our growth conditions. We identify the crystallographic orientations of Cs3Sb grown on graphene-coated 4H-SiC substrates and discuss the significance of examining the crystal structure of these films for growing epitaxial heterostructures in future experiments.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Changes in soil water content and lateral flow exert large effects on soil thermal dynamics across Alaskan landscapes

Both lateral surface and subsurface water flow affect soil moisture dynamics, yet most land surface models only solve subsurface water movement vertically. Here, we use a 3D ecosystem model that considers both land surface and subsurface hydrologic processes to simulate soil moisture, which is then used to drive a 1-D vertical soil thermal model to simulate the soil moisture effects on soil thermal dynamics in central Alaska. Our coupled model improves soil temperature (ST) estimates by 43.5% in comparison with observational data. Soil moisture has little effect on ST during the wet season (-1.5%) and a substantial influence during the dry season (60%). Spatially, water lateral flow has significant impacts on both soil moisture and ST, causing model estimates for thawed areas in the transition season to increase by ~10% in the study area. Our results highlight the importance of considering dynamical soil moisture, as well as lateral flow effects, on soil thermal dynamics in permafrost regions.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Role of underlying surface, rainstorm and antecedent wetness condition on flood responses in small and medium sized watersheds in the Yangtze River Delta region, China

Floods are becoming more frequent and are hard to control due to the shortage of water conservancy projects in small and medium sized basins, especially in developing regions. Understanding the hydrologic responses and estimated flood characteristics to storm events can help to predict flood disasters and form better effective mitigation and adaptation strategies. Here, using observations of several representative watersheds and Artificial Neural Networks (ANN) and Principal Component Regression (PCR) models, we conducted data-driven analyses to examine the flood responding characteristics. We quantified the relative contributions of the influencing factors to the variation of each flood characteristic. Statistical analysis of the observations shows that the drainage area plays a key role in determining the distribution of lag time and peak discharge. Rainstorm variability has direct influence on floods, and typhoon-induced rainstorms with high total rainfall and rainfall intensity generate higher lag time, flood peak, unit discharge and runoff depth, but lower runoff coefficient. The ANN and PCR models accurately predicted the variations of flood features using the driving factors including physical geographical characteristics, rainstorm features, and antecedent condition. Physical geographic characteristics are key influential factors of lag time, flood peak and runoff coefficient, while the rainstorm features control the magnitude of unit discharge and runoff depth. These results indicate that floods are mainly affected by rainstorm features and physical geographic characteristics in the Yangtze River delta, and it might become more damaging with the increasing rainfall extremes and sprawling impervious surfaces in a changing environment.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Observation-Based Evaluation of Flood Estimation Techniques for a Small Snow-Dominated Basin in the Washington Cascade Mountains

Here, this study examines the application of the recently developed next-generation intensity-duration-frequency (NG-IDF) curves in hydrological design, focusing on a small snow-dominated basin in Washington state. Four methods are used to assess the NG-IDF performance: (1) basin outlet flood frequency analysis, (2) use of standard precipitation-based intensity-duration-frequency (PREC-IDF) curves following surface water design manuals typically used in the basin, (3) utilization of locally constructed PREC-IDF curves, and (4) use of locally constructed NG-IDF curves. The standard PREC-IDF design method assumes precipitation as rainfall and neglecting snowmelt or rain-on-snow (ROS) events that can lead to significant flood underestimations in the test basin. In contrast, the NG-IDF method incorporates snow processes and shows promising improvements in accurately estimating design floods. The validation analysis demonstrates the superiority of NG-IDF over standard and local PREC-IDF in this test basin. The study highlights the necessity for adjustments in current design manuals to ensure sufficient flood protection, particularly in light of the planned substantial investments in US infrastructure.

13 HYDRO ENERGY↗

DOE OSTI2021

Greater committed warming after accounting for the pattern effect

Our planet’s energy balance is sensitive to spatial inhomogeneities in sea surface temperature and sea ice changes, but this is typically ignored in climate projections. Here, we show the energy budget during recent decades can be closed by combining changes in effective radiative forcing, linear radiative damping and this pattern effect. The pattern effect is of comparable magnitude but opposite sign to Earth’s net energy imbalance in the 2000s, indicating its importance when predicting the future climate on the basis of observations. Additionally, after the pattern effect is accounted for, the best-estimate value of committed global warming at present-day forcing rises from 1.31 K (0.99–2.33 K, 5th–95th percentile) to over 2 K, and committed warming in 2100 with constant long-lived forcing increases from 1.32 K (0.94–2.03 K) to over 1.5 K, although the magnitude is sensitive to sea surface temperature dataset. Further constraints on the pattern effect are needed to reduce climate projection uncertainty.

58 GEOSCIENCES↗

DOE OSTI2020

A Rapid Sequential Separation Method for Determination of Actinides and TENORM in Fracking Wastes - 20223

With recent advances in unconventional drilling technology in the US and around the world, the risks of environmental contamination and exposure due to technologically enhanced naturally occurring radioactive materials (TENORM) from fracking wastes have also surfaced. Although the Permian Basin (southeastern New Mexico, western Texas) has long been a modest producer of oil, the advent of fracking technology a decade ago turned it into hot property for producers. A 2018 assessment of undiscovered, technically recoverable continuous oil and gas resources by the U.S. Geological Survey estimates an average 46.3 billion barrels of oil and 281 trillion cubic feet of gas. This is likely to increase the use of unconventional drilling and TENORM generation. TENORM concentrations in oil and gas exploration and production waste can be several hundred to several thousand times higher than background TENORM concentrations. Both the thorium and uranium decay chains contribute to airborne radionuclides arising from the radon gas escaping the ground and subsequently decaying as airborne particulates. Additionally, radon decay products {sup 210}Pb and {sup 210}Po can build up in scale on the internal surfaces of oil and gas handling pipes and in sludge in refineries, becoming potential inhalation and ingestion hazards for workers. Furthermore, southeastern NM is also home to world's only licensed and operating transuranic nuclear waste repository, the DoE's Waste Isolation Pilot Plant (WIPP). Plutonium isotopes ({sup 239+240}Pu) and {sup 241}Am, are expected to account for more than 99% of the total radioactivity scheduled for disposal in the WIPP repository. Thus, an improved understanding of the environmental fate and transport of TENORM, liberated by unconventional drilling, is essential to assess how best to protect individuals and the environment. In this context, accurate measurement of TENORM and actinides in environmental and biological samples is essential. In this presentation, a new sequential method for the separation and pre-concentration of actinides (Pu, Am, Np) and TENORM (Po, U and Th) derived from oil and gas exploration is proposed. The TEVA method involves a rapid co-precipitation step to remove matrix interferences from the samples, followed by plutonium oxidation state adjustment to Pu (IV) and an incubation period of ∼ 1 hour at 50-60 deg. C to allow the resultant Po (II) to oxidize into Po(IV). The polonium, neptunium, thorium and plutonium are then separated on a TEVA column, while americium and uranium are separated on a TRU column. After separation, the alpha counting source was prepared by micro-precipitation with copper sulfide (CuS) for polonium and neodymium fluoride (NdF{sub 3}) for actinides. The efficiency and reliability of the procedures were tested by analyzing filter, drinking water and frack sand samples. The method is simple, robust and can be performed quickly with excellent removal of interferences, high chemical recovery and very good alpha peak resolution. (authors)

07 ISOTOPE AND RADIATION SOURCES↗

DOE OSTI2024

Within‐field soil moisture variability and time‐invariant spatial structures of agricultural fields in the US Midwest

Abstract Understanding soil moisture variability and estimating high‐resolution soil moisture at subfield to field scales is critical for agricultural research and applications. However, systematic investigation of subfield scale soil moisture variability over cropland is still lacking from both measurement and satellite remote sensing. In this study, we aim to investigate (1) the characteristics of within‐field soil moisture distribution over typical cropland in the US Midwest and (2) the capabilities of satellite remote sensing in capturing the spatiotemporal variabilities of soil moisture at subfield scale. Specifically, we conducted soil moisture field experiments in three typical commercial agricultural fields (∼85 acres per field) in central Illinois, representing typical commercial farmlands in the US Midwest, and compared the soil moisture measurements with satellite remote sensing data from optical and active microwave sensors. In each field, dense soil moisture samples (spaced at 50–60 m) were obtained for two dry down events in May and July 2021, and multiple long‐term soil moisture stations were installed. We found prominent time‐invariant spatial structures of soil moisture at within‐field scales both during the dry down period and over longer time scales, and the stability is minimally affected by plant water use during the growing season. Comparing the field campaign measurements with satellite remote sensing data, we found that surface reflectance of shortwave infrared bands, such as SWIR1 (1610 nm) from Sentinel‐2, can capture relative surface soil moisture patterns at within‐field scales, but their relationships with soil moisture are field specific. These findings and the improved understanding of within‐field soil moisture dynamics could potentially help future research on high‐resolution soil moisture estimation with multi‐source remote sensing data.

Yang, Yi↗

DOE OSTI2025

Joint Modeling of Wind Speed and Wind Direction Through a Conditional Approach

Atmospheric near surface wind speed and wind direction play an important role in many applications, ranging from air quality modeling, building design, wind turbine placement to climate change research. It is therefore crucial to accurately estimate the joint probability distribution of wind speed and direction. In this work, we develop a conditional approach to model these two variables, where the joint distribution is decomposed into the product of the marginal distribution of wind direction and the conditional distribution of wind speed given wind direction. To accommodate the circular nature of wind direction, a von Mises mixture model is used; the conditional wind speed distribution is modeled as a directional dependent Weibull distribution via a two-stage estimation procedure, consisting of a directional binned Weibull parameter estimation, followed by a harmonic regression to estimate the dependence of the Weibull parameters on wind direction. A Monte Carlo simulation study indicates that our method outperforms two other approaches in estimation efficiency: one that utilizes periodic spline quantile regression and another that generates data from the commonly used Abe-Ley distribution for cylindrical data. We illustrate our method by using the output from a regional climate model to investigate how the joint distribution of wind speed and direction may change under some future climate scenarios. Our method indicates significant changes in the variation of wind speed with respect to some directions.

17 WIND ENERGY↗

DOE OSTI2023

Scalable computations for nonstationary Gaussian processes

Nonstationary Gaussian process models can capture complex spatially varying dependence structures in spatial datasets. However, the large number of observations in modern datasets makes fitting such models computationally intractable with conventional dense linear algebra. In addition, derivative-free or even first-order optimization methods can be very slow to converge when estimating many spatially varying parameters. In this paper, we present a computational framework which couples an algebraic block diagonal plus low-rank covariance matrix approximation with stochastic trace estimation to facilitate the efficient use of second-order solvers for maximum likelihood estimation of Gaussian process models with many parameters. We demonstrate the effectiveness of these methods by simultaneously fitting 192 parameters in the popular nonstationary model of Paciorek and Schervish using 107,600 sea surface temperature anomaly measurements.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2021

Protecting building occupants against the inhalation of outdoor-origin aerosols

During normal operations, buildings can protect their occupants from outdoor airborne particle hazards of all types, including airborne pollutants. A long-term international research effort has advanced our knowledge of building protection physics. Recently we have developed an operationally efficient, regional-scale methodology - Regional Shelter Analysis - to account for both building protection effects and the typical distribution of people in and among buildings. To provide input to this capability, we estimate here the degree of protection afforded by the currently existing US building stock. Here, we first assemble and summarize the published literature relevant to indoor particle losses including (a) deposition to indoor surfaces, (b) losses that occur when particles penetrate through the building envelope, and (c) heating, ventilation and air conditioning (HVAC) system filtration efficiencies as well as general building operating conditions. Building protection against inhaling particulate hazards varies strongly, by orders of magnitude, according to particle size, airborne particle loss rate, and to a lesser extent building use (occupancy). Protection increases modestly as particle size increases from 0.1 to 1 μm and significantly as particle size increases from 1 to 10 μm. Model results are placed in context with previously reported measurements. Suggestions for future work, including enhanced validation datasets are provided.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗

DOE OSTI2023

Quantifying uncertainty for deep learning based forecasting and flow-reconstruction using neural architecture search ensembles

Classical problems in computational physics such as data-driven forecasting and signal reconstruction from sparse sensors have recently seen an explosion in deep neural network (DNN) based algorithmic approaches. However, most DNN models do not provide uncertainty estimates, which are crucial for establishing the trustworthiness of these techniques in downstream decision making tasks and scenarios. In recent years, ensemble-based methods have achieved significant success for the uncertainty quantification in DNNs on a number of benchmark problems. However, their performance on real-world applications remains under-explored. In this work, we present an automated approach to DNN discovery and demonstrate how this may also be utilized for ensemble-based uncertainty quantification. Specifically, we propose the use of a scalable neural and hyperparameter architecture search for discovering an ensemble of DNN models for complex dynamical systems. We highlight how the proposed method not only discovers high-performing neural network ensembles for our tasks, but also quantifies uncertainty seamlessly. This is achieved by using genetic algorithms and Bayesian optimization for sampling the search space of neural network architectures and hyperparameters. Subsequently, a model selection approach is used to identify candidate models for an ensemble set construction. Afterwards, a variance decomposition approach is used to estimate the uncertainty of the predictions from the ensemble. We demonstrate the feasibility of this framework for two tasks — forecasting from historical data and flow reconstruction from sparse sensors for the sea-surface temperature. In conclusion, we demonstrate superior performance from the ensemble in contrast with individual high-performing models and other benchmarks.

Deep ensembles↗

DOE OSTI2019

Climate Forcing and Trends of Organic Aerosols in the Community Earth System Model (CESM2)

The Community Earth System Model version 2 (CESM2) includes three main atmospheric configurations: the Community Atmosphere Model version 6 (CAM6) with simplified chemistry and a simplified organic aerosol (OA) scheme, CAM6 with comprehensive tropospheric and stratospheric chemistry representation (CAM6-chem), and the Whole Atmosphere Community Climate Model version 6 (WACCM6). Both, CAM6-chem and WACCM6 include a more comprehensive secondary organic aerosols (SOA) approach using the volatility basis set (vbs) scheme and prognostic stratospheric aerosols. This paper describes the different OA schemes available in the different atmospheric configurations of CESM2 and discusses differences in aerosol burden and resulting climate forcings. Derived OA burden and trends differ due to differences in OA formation using the different approaches. Regional differences in Aerosol Optical Depth with larger values using the comprehensive approach occur over SOA source regions. Stronger increasing SOA trends between 1960 and 2015 in WACCM6 compared to CAM6 are due to increasing biogenic emissions aligned with increasing surface temperatures. Using the comprehensive SOA approach further leads to improved comparisons to aircraft observations and SOA formation of ˜143 Tg/yr. We further use WACCM6 to identify source contributions of OA from biogenic, fossil fuel, and biomass burning emissions, to quantify SOA amounts and trends from these sources. Increasing SOA trends between 1960 and 2015 are the result of increasing biogenic emissions aligned with increasing surface temperatures. Biogenic emissions are at least two thirds of the total SOA burden. In addition, SOA source contributions from fossil fuel emissions become more important, with largest values over Southeast Asia. The estimated total anthropogenic forcing of OA in WACCM6 for 1995–2010 conditions is -0.43 W/m2, mostly from the aerosol direct effect.

Tilmes, S↗