Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “history variables”

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 163 records · Page 9

Optimization and application of riblets for turbulent drag reduction

Riblet surfaces have been tested in boundary layers having different upstream histories and at higher Reynolds numbers than previously reported. The drag reduction for the riblet surfaces was found to be dependent on the height and spacing of the riblets in law-of-the-wall variables regardless of the free-stream Reynolds number or upstream boundary-layer history. Micro-photographs of the actual riblet geometries are examined to determine the effect of rib details on the riblet drag-reduction performances. To further increase drag-reduction performance, riblet surfaces are combined with another drag-reduction concept, the large-eddy breakup device (LEBU). In addition, the yaw sensitivity of riblets is evaluated, as well as the characteristics of riblet surfaces manufactured out of a thin vinyl sheet.

Walsh, M. J.↗

Estimating ocean production from satellite-derived chlorophyll - Insights from the EASTROPAC data set

The EASTROPAC expedition took place in 1967-68 in the eastern tropical Pacific Ocean. Primary production was related to near-surface chlorophyll in these data. Much of the variability in the relation was due to the light-history of the phytoplankton and its photoadaptive state. This was due to changes in the depth of mixing of the surface waters more than changes in insolation. Accurate estimates of production from satellite chlorophyll measurements may require knowledge of the temporal and spatial variation in mixing of this region.

Eppley, R. W.↗

Geologic Mapping of the Lunar South Pole Quadrangle (LQ-30)

In this study we use recent image, spectral and topographic data to map the geology of the lunar South Pole quadrangle (LQ-30) at 1:2.5M scale [1-7]. The overall objective of this research is to constrain the geologic evolution of LQ-30 (60 -90 S, 0 - 180 ) with specific emphasis on evaluation of a) the regional effects of impact basin formation, and b) the spatial distribution of ejecta, in particular resulting from formation of the South Pole-Aitken (SPA) basin and other large basins. Key scientific objectives include: 1) Determining the geologic history of LQ-30 and examining the spatial and temporal variability of geologic processes within the map area. 2) Constraining the distribution of impact-generated materials, and determining the timing and effects of major basin-forming impacts on crustal structure and stratigraphy in the map area. And 3) assessing the distribution of potential resources (e.g., H, Fe, Th) and their relationships with surface materials.

Mest, S. C.↗

Stationarity of the Tropical Pacific Teleconnection to North America in CMIP5 PMIP3 Model Simulations

The temporal stationarity of the teleconnection between the tropical Pacific Ocean and North America (NA) is analyzed in atmosphere-only, and coupled last-millennium, historical, and control runs from the Coupled Model Intercomparison Project Phase 5 data archive. The teleconnection, defined as the correlation between December-January-February (DJF) tropical Pacific sea surface temperatures (SSTs) and DJF 200 mb geopotential height, is found to be nonstationary on multidecadal timescales. There are significant changes in the spatial features of the teleconnection over NA in continuous 56-year segments of the last millennium and control simulations. Analysis of atmosphere-only simulations forced with observed SSTs indicates that atmospheric noise cannot account for the temporal variability of the teleconnection, which instead is likely explained by the strength of, and multidecadal changes in, tropical Pacific Ocean variability. These results have implications for teleconnection-based analyses of model fidelity in simulating precipitation, as well as any reconstruction and forecasting efforts that assume stationarity of the observed teleconnection.

histories↗

A brief review of the evidence for solar variability on the planets

An outline of the most recent and complete reviews on the history of Martian climate is presented and compared to the history of terrestrial climate. Suggestions are made on how solar luminosity changes may have affected both planets. Observations of the albedo of Titan occurring over a solar cycle are discussed, and the solar mechanisms that might be responsible for the observed albedo changes are considered.

Toon, O. B.↗

NASA/GEWEX SRB Surface Radiation Budget Fluxes Through the Prism of Weather States

The NASA/GEWEX Surface Radiation Budget Version 4 (SRB Rel4) product is now publicly available, covering the period from July 1983 through June 2017. This supersedes the SRB Rel3 (Stackhouse et al., 2011) product which has been used in the community for a wide variety of applications, including climate model validation, agriculture, solar energy, and architecture. SRB Rel4 uses the newly recalibrated and processed ISCCP HXS product as its primary input for cloud and radiance data, replacing ISCCP DX with a ninefold increase in pixel count (10km instead of 30km). This version retains a 1°x1° resolution but benefits from a much larger number of samples per grid box than the SRB Rel3. ISCCP also provides an atmospheric temperature and moisture dataset known as nnHIRS which we use here, along with Seaflux and Landflux surface and near-surface meteorological parameters. Rel4 incorporates several important algorithm improvements. These include recalculated shortwave (SW) atmospheric transmissivities and reflectivities yielding a somewhat less transmissive atmosphere. Both shortwave and longwave (LW) now also include variable aerosol composition and radiative properties, allowing for the use of a detailed aerosol history from the Max Planck Institute Aerosol Climatology (MACv1). LW and SW algorithms now produce pristine sky fluxes, allowing the aerosol flux effects to be quantified. For SW, ocean albedo and snow/ice albedo are improved from Release 3. Total solar irradiance is now variable, and reduced to an average of 1361 Wm-2. The radiative treatment of ice cloud is improved. For the LW, a climatological monthly varying spectral surface emissivity is added. Here we evaluate the SRB Rel4 top of atmosphere (TOA) and surface fluxes in the context of weather states and oceanic regions. Weather states (Tselioudis et al., 2013, Tselioudis et al., 2021) are defined by K-means clustering 2-D histograms of satellite-retrieved cloud optical depths and cloud top pressures. The most recent (Tselioudis et al., 2021) weather states derived from the International Satellite Cloud Climatology Project (ISCCP) H-series data results in eight cloud weather states and one clear sky weather state, for a total of nine weather states. We examine the statistics of SRB Rel4 fluxes for each weather state and a variety of relevant land and ocean regions. We compare to similar analyses performed on CERES EBAF and SYN1Deg flux products, and validate against Baseline Surface Radiometer Network (BSRN) land stations and Pacific Marine Environmental Laboratory (PMEL) ocean buoy data. It is demonstrated that the weather state concept is valuable when examining the comparative strengths and weaknesses of satellite radiative flux algorithms.

Atmospheric Radiation↗

GEWEX SRB Release 4: Public Release

The NASA/GEWEX Surface Radiation Budget (SRB) project produces 3-hourly shortwave and longwave surface and top of atmosphere radiative fluxes for the 1983-nearpresent time period. Here we announce the public availability of the new Release 4 Integrated data product (R4-IP). R4-IP uses the newly recalibrated and processed ISCCP HXS product as its primary input for cloud and radiance data, replacing ISCCP DX with a ninefold increase in pixel count (10km instead of 30km). This version retains a 1°x1° resolution but benefits from a much larger number of samples per grid box than the SRB Release 3. ISCCP also provides an atmospheric temperature and moisture dataset known as nnHIRS which we use here, along with Seaflux and Landflux surface and near-surface meteorological parameters constituting an “Integrated Product” for energy and water cycle studies. In addition to the input data improvements, several important algorithm improvements have been made since Release 3. These include recalculated shortwave (SW or solar wavelengths) atmospheric transmissivities and reflectivities yielding a somewhat less transmissive atmosphere. Both SW and LW (longwave or thermal infrared) also include variable aerosol composition and radiative properties, allowing for the use of a detailed aerosol history from the Max Planck Institute Aerosol Climatology (MAC). Both LW and SW algorithms now produce pristine sky fluxes, allowing the aerosol flux effects to be quantified. For SW, ocean albedo and snow/ice albedo are improved from Release 3. Total solar irradiance is now variable, and reduced to an average of 1361 Wm-2. The radiative treatment of ice cloud is improved. For the LW, a climatological monthly varying spectral surface emissivity is added.Here we analyze the new SW SRB datasets, comparing them to the previous Release 3, BSRN and PMEL surface measurements. Validation results show improved agreement compared to Release 3. Comparisons to ERBE and CERES TOA and surface satellite datasets before and after overlap periods show the long-term agreement with radiometric uncertainty. Monthly anomalies at global and zonal regions show very good correlation with the shorter ERBE and CERES flux anomalies linking those to the longer term. The uncertainties are discussed and periods of potential issues in inputs and/or algorithms are identified.

Earth energy budget↗

GEWEX SRB Release 4: Public Release

The NASA/GEWEX Surface Radiation Budget (SRB) project produces 3-hourly shortwave and longwave surface and top of atmosphere radiative fluxes for the 1983-near present time period. Here we announce the public availability of the new Release 4 Integrated data product (R4-IP). R4-IP uses the newly recalibrated and processed ISCCP HXS product as its primary input for cloud and radiance data, replacing ISCCP DX with a ninefold increase in pixel count (10km instead of 30km). This version retains a 1°x1° resolution but benefits from a much larger number of samples per grid box than the SRB Release 3. ISCCP also provides an atmospheric temperature and moisture dataset known as nnHIRS which we use here, along with Seaflux and Landflux surface and near-surface meteorological parameters constituting an “Integrated Product” for energy and water cycle studies. In addition to the input data improvements, several important algorithm improvements have been made since Release 3. These include recalculated shortwave (SW or solar wavelengths) atmospheric transmissivities and reflectivities yielding a somewhat less transmissive atmosphere. Both SW and LW (longwave or thermal infrared) also include variable aerosol composition and radiative properties, allowing for the use of a detailed aerosol history from the Max Planck Institute Aerosol Climatology (MAC). Both LW and SW algorithms now produce pristine sky fluxes, allowing the aerosol flux effects to be quantified. For SW, ocean albedo and snow/ice albedo are improved from Release 3. Total solar irradiance is now variable, and reduced to an average of 1361 Wm-2. The radiative treatment of ice cloud is improved. For the LW, a climatological monthly varying spectral surface emissivity is added. Here we analyze the new SW SRB datasets, comparing them to the previous Release 3, BSRN and PMEL surface measurements. Validation results show improved agreement compared to Release 3. Comparisons to ERBE and CERES TOA and surface satellite datasets before and after overlap periods show the long-term agreement with radiometric uncertainty. Monthly anomalies at global and zonal regions show very good correlation with the shorter ERBE and CERES flux anomalies linking those to the longer term. The uncertainties are discussed and periods of potential issues in inputs and/or algorithms are identified.

Earth Radiation Budget↗

Identifications of RR Lyrae Stars and Quasars from the Simulated Data of Mephisto-W Survey

We have investigated the feasibilities and accuracies of the identifications of RR Lyrae stars and quasars from the simulated data of the Multi-channel Photometric Survey Telescope (Mephisto) W Survey. Based on the variable sources light curve libraries from the Sloan Digital Sky Survey (SDSS) Stripe 82 data and the observation history simulation from the Mephisto-W Survey Scheduler, we have simulated the uvgriz multi-band light curves of RR Lyrae stars, quasars and other variable sources for the first-year observation of Mephisto W Survey. We have applied the ensemble machine learning algorithm Random Forest Classifier (RFC) to identify RR Lyrae stars and quasars, respectively. We build training and test samples and extract ~150 features from the simulated light curves and train two RFCs respectively for the RR Lyrae star and quasar classification. We find that, our RFCs are able to select the RR Lyrae stars and quasars with remarkably high precision and completeness, with purity = 95.4% and completeness = 96.9% for the RR Lyrae RFC and purity = 91.4% and completeness = 90.2% for the quasar RFC. In conclusion, we have also derived relative importances of the extracted features utilized to classify RR Lyrae stars and quasars.

(galaxies:) quasars: general↗

Altered ß-cell Prohormone Processing and Secretion in Type 1 Diabetes

Analysis of data from clinical cohorts and more recently from human pancreatic tissue, indicate that defects in prohormone processing are an early and persistent component of type 1 diabetes pathogenesis. In this Perspectives article, we review the current state of knowledge of alterations in islet prohormone expression and processing in type 1 diabetes, and consider the clinical impact of these findings. Lingering questions, including pathologic etiologies and consequences of altered prohormone expression and secretion in type 1 diabetes, and the natural history of circulating prohormone production in health and disease are considered. Finally, key steps required to move forward in this area are outlined, including longitudinal testing of relevant clinical populations, studies that probe the genetics of altered prohormone processing, the need for combined functional and histologic testing of human pancreatic tissues, continued interrogation of the intersection between prohormone processing and autoimmunity, and optimal assays or approaches for analysis. Successful resolution of these questions may offer the potential to use altered prohormone processing as a pathogenic anchor that can be used to cluster different endotypes enveloping a large set of variables, and inform therapeutic strategies aimed at personalized intervention in the natural history of type 1 diabetes.

Islets, Insulin, Proinsulin, Islet Amyloid Polypep↗

Seasonality of Biological and Physical Systems as Indicators of Climate Variation and Change

Evidence-based responses to climate change by society require operational and sustained information including biophysical indicator systems that provide up-to-date measures of trends and patterns against historical baselines. Two key components linking anthropogenic climate change to impacts on socio-ecological systems are the periodic inter- and intra-annual variations in physical climate systems (seasonality) and in plant and animal life cycles (phenology). We describe a set of national indicators that reflect sub-seasonal to seasonal drivers and responses of terrestrial physical and biological systems to climate change and variability at the national scale. Proposed indicators and metrics include seasonality of surface climate conditions (e.g., frost and freeze dates and durations), seasonality of freeze/thaw in freshwater systems (e.g., timing of stream runoff and durations of lake/river ice), seasonality in ecosystem disturbances (e.g., wildfire season timing and duration), seasonality in vegetated land surfaces (e.g., green-up and brown-down of landscapes), and seasonality of organismal life-history stages (e.g., timings of bird migration). Recommended indicators have strong linkages to variable and changing climates, include abiotic and biotic responses and feedback mechanisms, and are sufficiently simple to facilitate communication to broad audiences and stakeholders interested in understanding and adapting to climate change.

Seasonality↗

Machine learning surrogate of physics-based building-stock simulator for end-use load forecasting

Building energy models are used to simulate heat and mass transfer and estimate end-use load in buildings. With the proliferation of solar photovoltaics on residential and commercial buildings, increasingly, buildings are expected to provide grid services, for which accurate and computationally efficient building energy simulations and end-use load prediction are imperative. Existing building energy simulation tools, however, have significant computational overhead that make them less practical in real-time deployment for optimization, design, uncertainty quantification and control in building energy management systems. Here this article presents a data-driven machine learning model based on light gradient boosting method (LightGBM) as a surrogate for a physics-based simulator for residential buildings to predict end-use load. The machine learning based surrogate model accounts for time-series related variables, seasonality and trend component of end-use load, and history of end-use load. The accuracy of the surrogate model is assessed on the prediction of the load profiles of 100 different houses in Cook County, Illinois, USA. The LightGBM surrogate model is shown to reduce the root-mean-squared error by 53% relative to a reference decision tree (DT) based model reported previously in the literature. Moreover, the model predicts the load spikes and high-ramp rate events throughout the year which are often the Achilles heel of other models in the literature. The machine learning based surrogate model is demonstrated to be computationally efficient, with a ten-fold reduction in the computational time compared to a physics-based building energy simulation, and suitable for uncertainty analysis and real-time control of building characteristics in response to uncertainty.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

elm-diagnostics

elm-diagnostics is a Python package for computing diagnostic analyses and visualizations for the E3SM Land Model (ELM) component and is meant to support new feature development in ELM. The tool reads model history files and performs quantitative analyses including budget-closure checking, variable transformations, temporal aggregations, and statistical summaries to support model evaluation, validation, and scientific interpretation. The framework is designed for extensibility, with modular architecture enabling straightforward addition of new diagnostic methods, derived variables, analysis types, visualization approaches, and model-specific adaptations

Hoffman, Matt [Los Alamos National Laboratory]↗

Physics-Informed Machine Learning Model for Ceramic Matrix Composite Creep

A physics-informed recurrent neural network (RNN) based surrogate model is developed to emulate the nonlinear, time-dependent constitutive behavior of ceramic matrix composites (CMCs) driven by matrix damage and constituent creep at the microscale. Physics-informed constraints are introduced into the surrogate model through regularization to ground the prediction in physics and improve its predictive capabilities. Training data is generated using the high-fidelity generalized method of cells (HFGMC) approach which calls appropriate creep and damage models for each of the constituents. This coupling permits simulating the nonlinear behavior of CMCs based on constituent response at the microscale along with microstructural features such as fiber and porosity volume fraction and fiber radius. The microscale repeating unit cell is loaded under creep fatigue conditions to replicate the material loading experienced in a turbine engine. Therefore, the RNN-based surrogate model is tasked with predicting, as a function of variable input stress sequence, temperature, and microstructural features, the resulting strain history response while satisfying physical constraints related to creep rate, isochoric inelastic deformation, and strain energy density. The trained surrogate model is shown to effectively match the strain history over quantified distributions of microstructural features and relevant loading regimes and temperatures. Neural network based surrogate models can offer efficient alternatives to running computationally intensive multiscale material models to simulate the nonlinear response of large structural models. Therefore, the presented work provides evidence towards the feasibility of developing, training, and running such models for CMCs with complex microstructures, nonlinear time-dependent material response, and under non-monotonic loading conditions.

ceramic matrix composites↗

The line profile variable B stars

The observational status of the line profile variable B stars is summarized. The following areas are discussed: recent history; evolutionary status; line profile variations; line strength variations; and photometric variations.

Smith, M. A.↗

On the chemical composition of L-chondrites

Radiochemical neutron activation analysis of Ag, As, Au, Bi, Co, Cs, Ga, In, Rb, Sb, Te, Tl, and Zn and major element data in 14 L4-6 and 3 LL5 chondrites indicates that the L group is unusually variable and may represent at least 2 subgroups differing in formation history. Chemical trends in the S/Fe rich subgroup support textural evidence indicating late loss of a shock formed Fe-Ni-S melt; the S/Fe poor subgroup seemingly reflects nebular fractionation only. Highly mobile In and Zn apparently reflect shock induced loss from L chondrites. However, contrasting chemical trends in several L chondrite sample sets indicate that these meteorites constitute a more irregular sampling of, or more heterogeneous parent material than do carbonaceous or enstatite chondrites. Data for 15 chondrites suggest higher formation temperatures and/or degrees of shock than for LL5 chondrites.

Neal, C. W.↗

Going With the Flow: Using a Particle Dispersion Model to Reveal Links Between Ocean Ecosystems and Marine Aerosols

Marine biogenic particle contributions to atmospheric aerosol concentrations are not well understood though they are important for determining cloud optical and cloud nucleating properties. Here we examine the relationship between marine aerosol measurements with satellite and model fields of ocean biology and meteorological variables during the North Atlantic Aerosols and Marine Ecosystems Study (NAAMES). NAAMES consisted of four field campaigns between November 2015 and April 2018 that aligned with the four major phases of the annual phytoplankton bloom cycle. The FLEXPART Lagrangian particle dispersion model is used to connect these variables spatiotemporally to ship-based aerosol. We find that correlations between some aerosol measurements with satellite measured and modelled variables increase with increasing trajectory length. This indicates biological and meteorological processes over the air mass history are influential to measured particle properties. For example, results show organic aerosol mass is driven by biogenic volatile organic compound (VOC) emissions from photosynthesis by phytoplankton stocks during advection into the region. In contrast, primary marine aerosol (PMA) concentrations showed better correlations to variables weighted with shorter air mass residence times, which reflects their localized origin as primary emissions. Evidence also suggest variability in PMA concentrations likely play an important role in VOC emission removal. The removal of VOCs lessen their impact on particle number and mass concentrations. The sensitivity of marine aerosols to the main ecosystem-atmosphere drivers and its dependence on air mass history are to be further discussed.

Kevin J Sanchez↗

Sensitivity analysis of homogenized cross section in AP1000 lattices

The two-step method for light water reactor simulation consists of performing lattice-level calculations to determine homogenized properties of the lattice for a variety of configurations and burnups then performing a core-level calculation which relies on those pre-calculated lattice properties. Calculating the homogenized lattice properties for the specific conditions needed in the core-level calculation relies on interpolating from the pre-calculated lattice properties. Although many studies have explored different models that can be used for this interpolation, there is a need to explore how to appropriately parameterize the lattice for those interpolation models. The present study uses linear sensitivity methods to determine the sensitivity of homogenized cross sections to both instantaneous and historical values of state variables. The results from this study can be used to inform parameterizations which more appropriately capture history effects in homogenized cross section interpolation. Two different lattices are used for this analysis from the AP1000 reactor, one includes burnable absorbers. It was found that early in the cycle, the historical values of state variables have little effect on the instantaneous value of the homogenized cross sections explored here - especially in the case of the lattice containing burnable absorbers. However, it was found that later in the cycle, the thermal fission homogenized cross section was sensitive to the historic states of the lattice. In fact, using the average of a state variable as a predictor for interpolation models may be insufficient for capturing historic effects due to more recent states having larger sensitivity measures than less recent states. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗