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At least 1,279 records · Page 71
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Uptake, Efflux, and Sequestration of Mercury in the Asian Clam, Corbicula fluminea , at Environmentally Relevant Concentrations, and the Implications for Mercury Remediation

(1) Mercury (Hg) is a persistent, ubiquitous contaminant that readily biomagnifies into higher trophic level species in aquatic environments across the globe. It is crucial to understand the movement of environmentally relevant concentrations of Hg in impacted freshwater streams to minimize risks to ecological and human health. (2) The bioconcentration kinetics of aqueous Hg exposure (20, 100, and 200 ng/L) in the invasive Asian Clam, Corbicula fluminea, were measured. A toxicokinetic model, the first parameterized for Hg accumulation in freshwater clams, was developed to estimate uptake and efflux parameters and compared to previous parameter values estimated for other mollusk species. (3) Results demonstrated that even at low Hg concentrations, Corbicula record signals of contamination through bioconcentration, and both direct measurement and toxicokinetic models demonstrate large Hg bioconcentration factors (as high as 1.34 × 10 5 mL/g dry tissue), similar to partitioning coefficients seen in engineered Hg sorbents. (4) Our study found that Corbicula accumulated Hg at aqueous concentrations relevant to impacted streams, but well below regulatory drinking water limits, demonstrating their utility as a sensitive sentinel species and potential bioremediator.

bioaccumulation↗
NASA NTRS2002

Cloud-Scale Numerical Modeling of the Arctic Boundary Layer

The research objective of this NASA grant-funded project was to determine in detail how large-scale processes. in combination with cloud-scale radiative, microphysical, and dynamical processes, govern the formation and multi-layered structure of Arctic stratus clouds. This information will be useful for developing and improving 1D (one dimensional) boundary layer models for the Arctic. Also, to quantitatively determine the effects of leads on the large-scale budgets of sensible heat, water vapor, and condensate in a variety of Arctic winter conditions. This information will be used to identify the most important lead-flux processes that require parameterization in climate models. Our approach was to use a high-resolution numerical model, the 2D (two dimensional) University of Utah Cloud Resolving Model (UU CRM), and its 1D version, the University of Utah Turbulence Closure Model (UU TCM), a boundary layer model based on third-moment turbulence closure, as well as a large-eddy simulation (LES) model originally developed by C.H. Moeng.

Kruegen, Steven K.↗
DOE OSTI2023

Model for the Softening Factor within Stages of Work Hardening

A formulation for a dimensionless coefficient c b is derived that represents a scale of microstructural softening for alloys which follow Kocks-Mecking (K-M) work hardening behavior. The variation of the true plastic strain ε p between the proportional limit σ y and the strength σ u at the instability is determined using the Considère criterion. Parameterization of the model is limited to variables expressly measured within tensile experiments. Further development is now made for the softening factor c bi through the individual and sequential stages 3 and 4 of plastic deformation during K-M work hardening Q behavior. Application is shown for tensile test results of Ti-6Al-4V made by different additively manufactured (AM) processes. It is found that the variation in plastic strain as a function of c bi produces a continuous curve representative of the alloy system. The results of data analysis indicate that Θ o3 and c b3 increase, while Θ o4 and c b4 decrease, as the total plastic strain ε p increases. Furthermore, formulations derived for K-M stages 3 and 4 enable the evaluation of other material parameters such as the activation volume ν* for the onset of plastic deformation. This activation volume is found to be near constant, at a ν*-value of 0.353±0.036 nm 3 as computed using a strain-rate sensitivity of strength exponent m of 0.014, irrespective of the AM method used to produce the Ti-6Al-4V alloy.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Optimal parameterizations for observational constraints on thawing dark energy

Time-varying dark energy is often modeled in observational analyses through generic parameterizations of its equation of state w(z), which typically use two free parameters {w 0 , w a } to span a broad range of behaviors as a function of redshift. However, this broad range of behaviors can only approximately capture the dynamics of any given microphysical theory of dark energy. A complementary approach is to use targeted parameterizations designed to model specific classes of dynamical dark energy with greater precision. Focusing on the class of thawing dark energy, we quantify and compare the precision with which nineteen generic and targeted parameterizations can capture the dynamics of physically motivated thawing quintessence theories. We find that a targeted parameterization derived from a Padé expansion of w is the most reliable of these, producing accurate reconstructions of w(z), the expansion history H(z), and cosmological parameters such as H 0 and Ω m for a broad range of microphysical theories.

dark energy experiments↗
DOE OSTI2014

A Physically Based Framework for Modelling the Organic Fractionation of Sea Spray Aerosol from Bubble Film Langmuir Equilibria

The presence of a large fraction of organic matter in primary sea spray aerosol (SSA) can strongly affect its cloud condensation nuclei activity and interactions with marine clouds. Global climate models require new parameterizations of the SSA composition in order to improve the representation of these processes. Existing proposals for such a parameterization use remotely-sensed chlorophyll-a concentrations as a proxy for the biogenic contribution to the aerosol. However, both observations and theoretical considerations suggest that existing relationships with chlorophyll-a, derived from observations at only a few locations, may not be representative for all ocean regions. We introduce a novel framework for parameterizing the fractionation of marine organic matter into SSA based on a competitive Langmuir adsorption equilibrium at bubble surfaces. Marine organic matter is partitioned into classes with differing molecular weights, surface excesses, and Langmuir adsorption parameters. The classes include a lipid-like mixture associated with labile dissolved organic carbon (DOC), a polysaccharide-like mixture associated primarily with semi-labile DOC, a protein-like mixture with concentrations intermediate between lipids and polysaccharides, a processed mixture associated with recalcitrant surface DOC, and a deep abyssal humic-like mixture. Box model calculations have been performed for several cases of organic adsorption to illustrate the underlying concepts. We then apply the framework to output from a global marine biogeochemistry model, by partitioning total dissolved organic carbon into several classes of macromolecule. Each class is represented by model compounds with physical and chemical properties based on existing laboratory data. This allows us to globally map the predicted organic mass fraction of the nascent submicron sea spray aerosol. Predicted relationships between chlorophyll-\textit{a} and organic fraction are similar to existing empirical parameterizations, but can vary between biologically productive and non-productive regions, and seasonally within a given region. Major uncertainties include the bubble film thickness at bursting and the variability of organic surfactant activity in the ocean, which is poorly constrained. In addition, marine colloids and cooperative adsorption of polysaccharides may make important contributions to the aerosol, but are not included here. This organic fractionation framework is an initial step towards a closer linking of ocean biogeochemistry and aerosol chemical composition in Earth system models. Future work should focus on improving constraints on model parameters through new laboratory experiments or through empirical fitting to observed relationships in the real ocean and atmosphere, as well as on atmospheric implications of the variable composition of organic matter in sea spray.

bubble film↗
DOE OSTI2022

Riverine Plastic Pollution: Sampling and Analysis Methods

Riverine plastic pollution has been found in all major U.S. rivers, but the exact amount of plastic being released to the oceans has not been quantified. Field studies conducted in U.S. rivers have used a range of sampling and analysis techniques and rarely measured the mass of the plastic collected. Measurements of riverine plastic pollution are needed to calibrate and validate models used to estimate the U.S. riverine plastic emissions to the oceans. This report surveys measurement methods used to quantify riverine pollution and current estimates of U.S. riverine plastic pollution from measurements and models. Measurement methods include field sampling and laboratory analysis. Field sampling methods are described for large (macro) and small (micro) plastic particles. Laboratory analysis methods are described for macro and microplastic with an emphasis on the detailed characterization processes of microplastics. Waterborne leachate analysis is also briefly described. Three models are described that estimate plastic pollution based on mismanaged plastic waste in the river catchment basins. The models were validated and calibrated with global data sources. The data sources were predominantly outside of the U.S., where the magnitude and composition of plastic pollution is different than what is found in U.S. rivers. Comprehensive measurements of riverine plastics are needed not only to characterize the riverine plastic pollution, but also parameterize and validate models of plastic fate and transport. This report also describes five key U.S. rivers that span a range of sizes and environmental conditions that could be sampled to obtain data to support characterization and model development of plastic pollution from rivers to oceans. Sampling and analysis protocol recommendations are made to ensure the highest quality of data are collected in the five rivers.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2005

Aura MLS Cloud Measurements: First-Year Results

Aura MLS provides the first vertical upper tropospheric cloud profiling from space, enabling global survey of the vertical structure of cloud systems, with seasonal and geographical variations, needed to evaluate the way clouds are parameterized in global models, thereby contributing to the understanding of cloud-climate feedbacks, and improved weather and climate predictions. The vertical structure of cloud systems is fundamentally important for understanding how clouds affect both their regional and large-scale atmospheric and radiative environments. The regional cloud profiles provide a critical tests of important parameterizations that enable the calculation of radiative flux profiles and heating rates throughout the atmospheric column, which in turn also regulates the water and energy cycles in the upper troposphere

Microwave Limb Sounder (MLS)↗
DOE OSTI2013

Collaborative Research: Using Arm Observations & Advanced Statistical Techniques to Evaluate Cam3 Clouds for Development of Stochastic Cloud-Radiation

The long-range goal of several past and current projects in our DOE-supported research has been the development of new and improved parameterizations of cloud-radiation effects and related processes, using ARM data, and the implementation and testing of these parameterizations in global models. The main objective of the present project being reported on here has been to develop and apply advanced statistical techniques, including Bayesian posterior estimates, to diagnose and evaluate features of both observed and simulated clouds. The research carried out under this project has been novel in two important ways. The first is that it is a key step in the development of practical stochastic cloud-radiation parameterizations, a new category of parameterizations that offers great promise for overcoming many shortcomings of conventional schemes. The second is that this work has brought powerful new tools to bear on the problem, because it has been a collaboration between a meteorologist with long experience in ARM research (Somerville) and a mathematician who is an expert on a class of advanced statistical techniques that are well-suited for diagnosing model cloud simulations using ARM observations (Shen).

15 GEOTHERMAL ENERGY↗
NASA NTRS1993

The annual pressure cycle on Mars: Results from the LMD Martian atmospheric general circulation model

We have been developing a General Circulation Model (GCM) of the martian atmosphere since 1989. The model has been described rather extensively elsewhere and only the main characteristics are given here. The dynamical part of the model, adapted from the LMD terrestrial climate model, is based on a finite-difference formulation of the classical 'primitive equations of meteorology.' The radiative transfer code includes absorption and emission by CO2 (carefully validated by comparison to line-by-line calculations) and dust in the thermal range and absorption and scattering by dust in the visible range. Other physical parameterizations are included: modeling of vertical turbulent mixing, dry convective adjustment (in order to prevent vertical unstable temperature profiles), and a multilayer model of the thermal conduction in the soil. Finally, the condensation-sublimation of CO2 is introduced through specification of a pressure-dependent condensation temperature. The atmospheric and surface temperatures are prevented from falling below this critical temperature by condensation and direct precipitation onto the surface of atmospheric CO2. The only prespecified spatial fields are the surface thermal inertia, albedo, and topography.

Hourdin, Frederic↗
DOE OSTI2021

Metrics for evaluating tropical cyclones in climate data

This manuscript describes a software suite that can be used for objective evaluation of tropical cyclones (TCs) in gridded climate data. Using cyclone trajectories derived from 6-hourly data, a comprehensive set of metrics is defined to systematically compare and contrast products to one another. In addition to annual TC climatologies, attention is paid to spatial and temporal patterns of storm occurrence and intensity. Assessment can be performed either on the global scale or regional domains. Simple to visualize ‘scorecards’ allow for rapid credibility assessment. We showcase three key findings enabled by this suite. First, we compare the representation of TCs in seven current-generation global reanalyses and conclude that higher resolution models and those with TC-specific assimilation contain more accurate storm climatologies. Second, using a free-running Earth system model (ESM) we find that full basin refinement is required in variable-resolution configurations to adequately simulate North Atlantic TC frequency. Furthermore, upstream refinement over northern Africa offers little benefit in simulating storm occurrence but spatial genesis patterns are improved. Finally, we show that TCs simulated by ESMs can be highly sensitive to individual parameterizations in climate models, with North Atlantic TC metrics varying greatly depending on version of the Morrison-Gettelman microphysics package.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Differentiable Multiphysics Codes: A Breakthrough Technology for Simulation and Computing

This document summarizes the findings of a strategic planning exercise commissioned by the Weapons Simulation and Computing, Computational Physics (WSC/CP) program at the Lawrence Livermore National Laboratory (LLNL) in FY24. During the year, the committee met with multiple stakeholder communities to gather input, opinions, suggestions and concerns which have been incorporated throughout this document. The key findings from this exercise are summarized: • The development of multiphysics modelling and simulation (mod/sim) codes and software technologies, their deployment on exascale compute platforms, and their broad adoption across the NNSA is a major success of the Advanced Simulation and Computing (ASC) program and the Exascale Computing Project (ECP). Sustained investment in these core technologies is essential. • Today’s state of the art involves running ensembles of O(100K) simulations to perform uncertainty quantification (UQ) and design studies using multiple statistical methods such as Bayesian optimization to understand sensitivities of our models and explore parameterized design spaces. Even with exascale computing, we are practically limited to O(10) parameters in these studies since the number of simulations required to sample the space scales exponentially with the number of design parameters. • The data from these simulation ensembles is increasingly being used to train machine learned (ML) surrogates (or reduced order models, ROMs) which can then be used for optimization or real time design exploration. However, the trained surrogates are still limited in the number of parameters they can represent due to the sampling limitations previously noted. • Augmenting our suite of integrated multiphysics simulation codes, both current and emerging, with the ability to compute gradients (solution derivatives) of arbitrary simulation outputs with respect to (some or all) simulation inputs would be a breakthrough technology, opening the door to a new era of efficient and automated inverse design based on verified and validated mod/sim capabilities. • This capability, which we refer to as differentiable multiphysics codes (DMCs), would revolutionize both UQ and optimization studies by breaking the curse of dimensionality that presently limits our “gradient-free” ensemble based computing approach. A similar breakthrough occurred in the AI/ML community once the ability to compute gradients of arbitrary loss functions using back-propagation became commonplace. Gradient information from the multiphysics codes can also be used to dramatically improve the efficiency and scale of training of ML/ROM surrogates for rapid assessments. • Achieving this in our suite of codes will be a grand challenge, similar to the amount of effort that was required to transition from CPU to GPU computing. It will require buy-in from the entire WSC/CP program and beyond, including all integrated codes, physics and engineering models, third-party library dependencies and performance portability abstractions. It will also require investment in research and development of numerical methods for computing adjoints of coupled physics across multiple adaptively refined moving meshes and of stochastic (Monte Carlo) and mesh free (SPH) methods. • New software and numerical techniques, largely pioneered by the AI/ML community, make this feasible. Chief among these is automatic differentiation (AD), the ability to employ AD at point-wise locations in a physics calculation (instead of traditional black-box approaches) and the ability to perform “back-propagation in time” (or reverse mode AD) for non-linear partial differential equations (PDEs). Fundamentally, the conclusion of this strategic planning exercise is that the time is right to undertake a large scale effort in WSC, centered on the existing integrated codes, to continue the natural evolution of mod/sim in the age of AI/ML. Instead of attempting to replace mod/sim with purely data driven AI/ML models, we believe the key to success is to integrate AI/ML by building on top of the decades of hard-won knowledge and the verified/validated multiphysics modelling capability that is the hallmark of the ASC program.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Consequences of adsorbate-adsorbate interactions for apparent kinetics of surface catalytic reactions

Lateral adsorbate interactions at catalyst surfaces are known to influence adsorption energies and reaction rates. Lattice-based kinetic Monte Carlo (kMC) simulations are able to capture these influences, but such models are typically parameterized for a specific reaction network and catalyst surface. Here we report kMC simulations to probe the influence of lateral interactions on simulated rates, rate orders, apparent activation energies, and Sabatier plots. We construct a simple, two-step reaction network involving a single adsorbate and rate- limiting diatomic dissociation, employ a generic repulsive lateral interaction model consistent with known adsorbate-adsorbate interactions on metal surfaces, and a rate model consistent with known Brønsted-Evans-Polyani relationships for diatomic dissocations. Furthermore, we juxtapose reaction kinetics over a wide range of reaction conditions and catalyst binding energies, as a function of interaction strength. We find that at a given zero-coverage binding energy and external conditions, adsorbate coverage decreases monotonically with increasing interaction strength, but absolute rates can vary linearly or nonlinearly. Interactions flatten the Sabatier volcano and shift the maximum towards stronger binding. Influences on apparent rate orders and activation energies are modest and are sensitive to interaction-induced adsorbate ordering. Model predictions are sensitive to lattice size effects at high coverages. The results, modelled for a simple reaction system, highlight the generic consequences of lateral interactions and guidance for identifying their signatures in observed kinetics.

kinetic Monte Carlo↗
DOE OSTI2018

The importance of considering sub-grid cloud variability when using satellite observations to evaluate the cloud and precipitation simulations in climate models

Abstract. Satellite cloud observations have become an indispensable tool for evaluating general circulation models (GCMs). To facilitate the satellite and GCM comparisons, the CFMIP (Cloud Feedback Model Inter-comparison Project) Observation Simulator Package (COSP) has been developed and is now increasingly used in GCM evaluations. Real-world clouds and precipitation can have significant sub-grid variations, which, however, are often ignored or oversimplified in the COSP simulation. In this study, we use COSP cloud simulations from the Super-Parameterized Community Atmosphere Model (SPCAM5) and satellite observations from the Moderate Resolution Imaging Spectroradiometer (MODIS) and CloudSat to demonstrate the importance of considering the sub-grid variability of cloud and precipitation when using the COSP to evaluate GCM simulations. We carry out two sensitivity tests: SPCAM5 COSP and SPCAM5-Homogeneous COSP. In the SPCAM5 COSP run, the sub-grid cloud and precipitation properties from the embedded cloud-resolving model (CRM) of SPCAM5 are used to drive the COSP simulation, while in the SPCAM5-Homogeneous COSP run only grid-mean cloud and precipitation properties (i.e., no sub-grid variations) are given to the COSP. We find that the warm rain signatures in the SPCAM5 COSP run agree with the MODIS and CloudSat observations quite well. In contrast, the SPCAM5-Homogeneous COSP run which ignores the sub-grid cloud variations substantially overestimates the radar reflectivity and probability of precipitation compared to the satellite observations, as well as the results from the SPCAM5 COSP run. The significant differences between the two COSP runs demonstrate that it is important to take into account the sub-grid variations of cloud and precipitation when using COSP to evaluate the GCM to avoid confusing and misleading results.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2014

High-Fidelity Flash Lidar Model Development

NASA's Autonomous Landing and Hazard Avoidance Technologies (ALHAT) project is currently developing the critical technologies to safely and precisely navigate and land crew, cargo and robotic spacecraft vehicles on and around planetary bodies. One key element of this project is a high-fidelity Flash Lidar sensor that can generate three-dimensional (3-D) images of the planetary surface. These images are processed with hazard detection and avoidance and hazard relative navigation algorithms, and then are subsequently used by the Guidance, Navigation and Control subsystem to generate an optimal navigation solution. A complex, high-fidelity model of the Flash Lidar was developed in order to evaluate the performance of the sensor and its interaction with the interfacing ALHAT components on vehicles with different configurations and under different flight trajectories. The model contains a parameterized, general approach to Flash Lidar detection and reflects physical attributes such as range and electronic noise sources, and laser pulse temporal and spatial profiles. It also provides the realistic interaction of the laser pulse with terrain features that include varying albedo, boulders, craters slopes and shadows. This paper gives a description of the Flash Lidar model and presents results from the Lidar operating under different scenarios.

Hines, Glenn D.↗
DOE OSTI2019

GD358: Three Decades of Observations for the In-depth Asteroseismology of a DBV Star

Here, we report on the analysis of 34 years of photometric observations of the pulsating helium atmosphere white dwarf GD358. The complete data set includes archival data from 1982 to 2006, and 1195.2 hr of new observations from 2007 to 2016. From this data set, we extract 15 frequencies representing g-mode pulsation modes, adding 4 modes to the 11 modes known previously. We present evidence that these 15 modes are ℓ = 1 modes, 13 of which belong to a consecutive sequence in radial overtone k. We perform a detailed asteroseismic analysis using models that include parameterized, complex, carbon and oxygen core composition profiles to fit the periods. Recent spectroscopic analyses place GD358 near the red edge of the DBV instability strip, at 24,000 ± 500 K and a $\mathrm{log}\,{\text{}}g$ of 7.8 ± 0.08 dex. The surface gravity translates to a mass range of 0.455–0.540 ${M}_{\odot }$. Our best-fit model has a temperature of 23,650 K and a mass of 0.5706 ${M}_{\odot }$. That is slightly more massive than what is suggested by the most recent spectroscopy. We find a pure helium layer mass of 10–5.50, consistent with the result of previous studies and the outward diffusion of helium over time.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

Projected precipitation changes within the Great Lakes and Western Lake Erie Basin: a multi‐model analysis of intensity and seasonality

ABSTRACT The Great Lakes region encompasses the largest freshwater lake network in the world and supports a diverse network of agriculture, transportation, and tourism. Recently, Lake Erie has experienced increased hypoxia events, which have been attributed to agricultural practices and changes in run‐off. Here we examine the projected changes in extreme precipitation events to address concerns regarding regional agriculture, surface run‐off, and subsequent water quality. Precipitation projections within the overall Great Lakes Basin and the Western Lake Erie Basin subregion are examined using climate model simulations of varying spatial resolutions to understand historical precipitation and projected future precipitation. We develop three model ensembles for the historical period (1980–1999) and the mid‐century (2041–2060) that cover a range of spatial resolutions and future emissions scenarios, including: (1) 12 global model members from the fifth Climate Model Intercomparison Project ( CMIP5 ) using Representative Concentration Pathway ( RCP ) 8.5, (2) ten regional climate model ( RCM ) members from the North American Regional Climate Change Assessment Program driven by CMIP3 global models using the A2 emissions scenario, and (3) two high resolution RCM simulations ( RCM4 ) driven by CMIP5 global models using the RCP 8.5 scenario. For the historical period, all model ensembles overestimate winter and spring precipitation, and many of the models simulate a summer drying that is not observed. At mid‐century, most of the models predict a 10–20% increase in precipitation depending on the time of year. Daily probability distribution functions from three model ensembles reveal spring seasonal increases in high precipitation event probabilities when compared to the historical period, suggesting an increase in the frequency of high intensity precipitation at mid‐century. Overall, the presence of lakes or higher spatial resolution does not ensure improved representation of historical processes, and more complex interactions between large‐scale dynamics, local feedbacks, and physical parameterizations drive the model spread.

Basile, Samantha J.↗
DOE OSTI2017

A dislocation density-based continuum model of the anisotropic shock response of single crystal α-cyclotrimethylene trinitramine

Here, we have developed a model for the finite deformation thermomechanical response of α-cyclotrimethylene trinitramine (RDX). Our model accounts for nonlinear thermoelastic lattice deformation through a free energy-based equation of state developed by Cawkwell et al. (2016) in combination with temperature and pressure dependent elastic constants, as well as dislocation-mediated plastic slip on a set of slip systems motivated by experimental observation. The kinetics of crystal plasticity are modeled using the Orowan equation relating slip rate to dislocation density and the dislocation velocity developed by Austin and McDowell (2011), which naturally accounts for transition from thermally activated to dislocation drag limited regimes. Evolution of dislocation density is specified in terms of local ordinary differential equations reflecting dislocation–dislocation interactions. This paper presents details of the theory and parameterization of the model, followed by discussion of simulations of flyer plate impact experiments. Impact conditions explored within this combined simulation and experimental effort span shock pressures ranging from 1 to 3 GPa for four crystallographic orientations and multiple specimen thicknesses. Simulation results generated using this model are shown to be in strong agreement with velocimetry measurements from the corresponding plate impact experiments. Finally, simulation results are used to motivate conclusions about the nature of dislocation-mediated plasticity in RDX.

36 MATERIALS SCIENCE↗