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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.

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At least 901 records · Page 50
All sourcesNASA NTRSDOE OSTI
NASA NTRS2011

Multi-Decadal Change of Atmospheric Aerosols and their Effect on Surface Radiation

We present an investigation on multi-decadal changes of atmospheric aerosols and their effects on surface radiation using a global chemistry transport model, GOCART, along with the near-term to long-term data records. We focus on a 28-year time period of satellite era from 1980 to 2007 during which a suite of aerosol data from satellite observations, ground-based measurements, and intensive field experiments have become available. Particularly: (1) We compare the model calculated clear sky downward radiation at the surface with surface network data from BSRN and CMA (2) We compare the model and surface data with satellite derived downward radiation products from ISCCP and SRS (3) We analyze the long-term global and regional aerosol trends in major anthropogenic source regions (North America, Europe, Asia) that have been experiencing considerable changes of emissions during the three decades, dust and biomass burning regions that have large interannual variability, downwind regions that are directly affected by the changes in the source area, and remote regions that are considered to representing "background" conditions. The comparisons and methods from this study can be applied to multiple model analysis in the AeroCom framework.

Chin, Mian↗
NASA NTRS1979

A comparison of two accretional heating models

Models of accretional heating that include large-body impact effects are reviewed. Various details of the models are compared, as well as the results of their calculations. Within the uncertainties in the models, the results compare reasonably with each other, and a post-accretion moon with some melting in its outer layers, but not much towards the center, seems to be described by these analyses.

Ransford, G. A.↗
NASA NTRS2012

Multi-decadal Change of Atmospheric Aerosols and their Effect on Surface Radiation

We present an investigation on multi-decadal changes of atmospheric aerosols and their effects on surface radiation using a global chemistry transport model GOCART along with the near-term to long-term data records. We focus on a 28-year time period of satellite era from 1980 to 2007 during which a suite of aerosol data from satellite observations, ground-based measurements, and intensive field experiments have become available. Particularly: (1) We compare the model calculated clear sky downward radiation at the surface with surface network data from Baseline Surface Radiation Network (BSRN) and CMA (2) We compare the model and surface data with satellite derived downward radiation products from ISCCP and SRB (3) We analyze the long-term global and regional aerosol trends in major anthropogenic source regions (North America, Europe, Asia) that have been experiencing considerable changes of emissions during the three decades, dust and biomass burning regions that have large interannual variability, downwind regions that are directly affected by the changes in the source area, and remote regions that are considered to representing "background" conditions.

Chin, Mian↗
DOE OSTI2018

A coupled rate theory-Monte Carlo model of helium bubble evolution in plasma-facing micro-engineered tungsten

A multiscale model of helium bubble evolution in plasma-facing materials is developed. The model links different stages of helium bubble evolution: deposition, nucleation, growth, motion, and coalescence. Helium deposition is simulated with the SRIM Monte Carlo program to give spatial information on helium and displacement damage distributions near the surface. This deposition profile is then introduced into a space-dependent rate theory of bubble nucleation and growth to describe the early stages of the distribution and size of helium bubbles. The coarsening stage of bubble evolution as a result of whole bubble motion, interaction, and coalescence is modeled by a new Object Kinetic Monte Carlo (OKMC) model, for which initial conditions are taken from the mean-field rate theory calculations. The model is compared to experimental data on low-energy helium plasma interaction with micro-engineered tungsten (W), and on high-energy helium ion deposition in flat W samples. Novel features of the multiscale model include: (1) space-dependent rate theory; (2) OKMC model of bubble motion in stress and temperature fields; and (3) application of the model to micro-engineered materials, and comparison with experiments on the same time-scale. At low helium ion energy, it is found that the mechanism of trap mutation is essential in achieving good agreement with experimental measurements. On the other hand, good agreement with experiments at high incident ion energy and temperature showed the importance of bubble coalescence and coarsening as main mechanisms. The results of the model are compared with experiments on flat W surfaces irradiated at high ion energy (30 keV), and with micro-engineered W, where the surface is coated with high-density micro-pillars at low ion energy (around 100 eV). The predicted average bubble radius and density are in qualitative agreement with experimental results.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Comparison of structurally diverse simulation models for prediction of epidemic outcomes caused by a long-distance dispersed pathogen

Long-distance dispersal (LDD) pathogens pose substantial challenges for epidemic control due to their ability to generate new infection foci at great distances. While various modeling approaches have been developed to understand and manage such outbreaks, little work has compared how models of different structures behave under shared conditions. Here, in this study, we compare four structurally distinct epidemiological models — EPIMUL, GEMF, PoPS, and Warwick — each adapted to simulate the spread of wheat stripe rust (WSR), a wind-dispersed LDD pathogen, under identical epidemiological parameters and dispersal kernel. Using data from a controlled field experiment, we evaluate the ability of each model to replicate disease prevalence under nine intervention scenarios that vary in timing and culling area. While the models differ substantially in design — ranging from spatial grid-based to network-based and raster-based frameworks — the shared dispersal kernel allowed for close alignment in their predictions. All models accurately captured general epidemic trends, particularly the strong effect of early intervention on disease suppression. We qualitatively compared their behavioral responses across scenarios and also evaluated an ensemble prediction by averaging across model outputs. Our findings highlight how integrating shared epidemiological components into distinct modeling frameworks can improve consistency and accuracy, while reinforcing the importance of early culling in managing LDD pathogen outbreaks.

Dispersal kernel↗
DOE OSTI2022

Machine Learning with Gradient-Based Optimization of Nuclear Waste Vitrification with Uncertainties and Constraints

Gekko is an optimization suite in Python that solves optimization problems involving mixed-integer, nonlinear, and differential equations. The purpose of this study is to integrate common Machine Learning (ML) algorithms such as Gaussian Process Regression (GPR), support vector regression (SVR), and artificial neural network (ANN) models into Gekko to solve data based optimization problems. Uncertainty quantification (UQ) is used alongside ML for better decision making. These methods include ensemble methods, model-specific methods, conformal predictions, and the delta method. An optimization problem involving nuclear waste vitrification is presented to demonstrate the benefit of ML in this field. ML models are compared against the current partial quadratic mixture (PQM) model in an optimization problem in Gekko. GPR with conformal uncertainty was chosen as the best substitute model as it had a lower mean squared error of 0.0025 compared to 0.018 and more confidently predicted a higher waste loading of 37.5 wt% compared to 34 wt%. The example problem shows that these tools can be used in similar industry settings where easier use and better performance is needed over classical approaches. Future works with these tools include expanding them with other regression models and UQ methods, and exploration into other optimization problems or dynamic control.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
NASA NTRS2009

Validation of PICA Ablation and Thermal-Response Model at Low Heat Flux

Phenolic Impregnated Carbon Ablator (PICA) was the forebody heatshield material on the Stardust sample-return capsule and is also a primary candidate material for the Mars Science Lander (MSL), the Orion Crew Module, and the SpaceX Dragon vehicle. As part of the heatshield qualification for Orion, physical and thermal properties of virgin and charred PICA were measured, and an ablation and thermal response model was developed. We validated the model by comparing it with recession and temperature data from stagnation arcjet tests conducted over a wide range of stagnation heat flux of 107 to 1102 W/sq cm. The effect of orthotropic thermal conductivity was evident in the thermal response of the arcjet models. In general, model predictions compared well with the data; however, the uncertainty of the recession prediction was greatest for heat fluxes below 200 W/sq cm. More recent MSL testing focused on the low heat flux regime of 45 to 250 W/sq cm. The new results confirm the recession uncertainty, especially for pressures below 6 kPa. In this work we focus on improving the model predictions for MSL and Orion tests below 250 W/sq cm.

Milos, Frank S.↗
DOE OSTI2017

A comprehensive iso-octane combustion model with improved thermochemistry and chemical kinetics

Iso-Octane (2,2,4-trimethylpentane) is a primary reference fuel and an important component of gasoline fuels. Furthermore, it is a key component used in surrogates to study the ignition and burning characteristics of gasoline fuels. This paper presents an updated chemical kinetic model for iso-octane combustion. Specifically, the thermodynamic data and reaction kinetics of iso-octane have been re-assessed based on new thermodynamic group values and recently evaluated rate coefficients from the literature. The adopted rate coefficients were either experimentally measured or determined by analogy to theoretically calculated values. New alternative isomerization pathways for peroxy-alkyl hydroperoxide ($\dot{O}$OQOOH) radicals were added to the reaction mechanism. The updated kinetic model was compared against new ignition delay data measured in rapid compression machines (RCM) and a high-pressure shock tube. Our experiments were conducted at pressures of 20 and 40 atm, at equivalence ratios of 0.4 and 1.0, and at temperatures in the range of 632–1060 K. The updated model was further compared against shock tube ignition delay times, jet-stirred reactor oxidation speciation data, premixed laminar flame speeds, counterflow diffusion flame ignition, and shock tube pyrolysis speciation data available in the literature. Finally, the updated model was used to investigate the importance of alternative isomerization pathways in the low temperature oxidation of highly branched alkanes. When compared to available models in the literature, the present model represents the current state-of-the-art in fundamental thermochemistry and reaction kinetics of iso-octane; and thus provides the best prediction of wide ranging experimental data and fundamental insights into iso-octane combustion chemistry.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Effective hopping in holographic Bose and Fermi-Hubbard models

In this paper, we analyze a proposed gravity dual to a SU(N) Bose-Hubbard model, as well as construct a holographic dual of a SU(N) Fermi-Hubbard model from D-branes in string theory. In both cases, the SU(N) is dynamical, i.e. the hopping degrees of freedom are strongly coupled to SU(N) gauge bosons which themselves are strongly interacting. The vacuum expectation value (VEV) of the hopping term (i.e. the hopping energy) is analyzed in the gravity dual as a function of the bulk mass of the field dual to the hopping term, as well as of the coupling constants of the model. The bulk mass controls the anomalous dimension (i.e. the critical exponent) of the hopping term in the SU(N) Bose-Hubbard model. We compare the hopping energy to the corresponding result in a numerical simulation of the ungauged SU(N) Bose-Hubbard model. We find agreement when the hopping parameter is smaller than the other couplings. Our analysis shows that the kinetic energy increases as the bulk mass increases, due to increased contributions from the IR. The holographic Bose-Hubbard model is then compared with the string theory construction of a SU(N) Fermi-Hubbard model. The string theory construction makes it possible to describe fluctuations around a half-filled state in the supergravity limit, which map to O(1) occupation number fluctuations in the Fermi-Hubbard model at half filling. Finally, the VEV of the Bose-Hubbard model is shown to agree with the one of the fermionic Hubbard model with the help of a two-site version of the Jordan-Wigner transformation.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Going Off Grid: A Comparative Study of the Lagrangian and Eulerian Perspectives of New Particle Formation Events

New particle formation and growth (NPF&G) is the process by which ultrafine particles are formed from gas-phase precursors. NPF&G is the dominant source of global aerosol number with important influences on climate. Most observations of NPF&G events are conducted at stationary sites; however, NPF&G observed from stationary sites is influenced by gradual or rapid changes in the air masses passing over the site, complicating NPF&G analysis. In this work, we use observations and a 3D aerosol model to compare aerosol size distributions at a stationary site (Southern Great Plains [SGP] observatory, Oklahoma, USA) and along Lagrangian trajectories crossing the site. The model simulates the NPF&G events reasonably well at SGP. Using the model to compare the Lagrangian and stationary perspectives, we can explain previously unanalyzable days with some evidence of NPF&G as either non-event or analyzable NPF&G days. We find most of the unanalyzable NPF&G days are due to isolated and inhomogeneous NPF&G occurring upwind of the stationary site, often in the outflow of urban regions. Finally, we compare formation rates of 3 nm particles, growth rates, and the survival probability of 3 nm particles growing to 25 nm between the stationary and Lagrangian perspectives. Because of the much larger number of analyzable days along the Lagrangian trajectories, this perspective potentially provides more robust statistics and better characterization of NPF&G event extremes. Our method for extracting chemical/physical properties along Lagrangian trajectories from 3D models can be applied to a wide range of science questions.

O’Donnell, Samuel E. [Colorado State Univ., Fort C↗
DOE OSTI2016

Using Measured Plane-of-Array Data Directly in Photovoltaic Modeling: Methodology and Validation

Measured plane-of-array (POA) irradiance may provide a lower-cost alternative to standard irradiance component data for photovoltaic (PV) system performance modeling without loss of accuracy. Previous work has shown that transposition models typically used by PV models to calculate POA irradiance from horizontal data introduce error into the POA irradiance estimates, and that measured POA data can correlate better to measured performance data. However, popular PV modeling tools historically have not directly used input POA data. This paper introduces a new capability in NREL's System Advisor Model (SAM) to directly use POA data in PV modeling, and compares SAM results from both POA irradiance and irradiance components inputs against measured performance data for eight operating PV systems.

14 SOLAR ENERGY↗
NASA NTRS1990

Neural networks and MIMD-multiprocessors

Two artificial neural network models are compared. They are the Hopfield Neural Network Model and the Sparse Distributed Memory model. Distributed algorithms for both of them are designed and implemented. The run time characteristics of the algorithms are analyzed theoretically and tested in practice. The storage capacities of the networks are compared. Implementations are done using a distributed multiprocessor system.

Vanhala, Jukka↗
DOE OSTI2019

Pumped Storage Hydro Model Evaluation Report Task 1: Tool Assessment

Pumped storage hydro (PSH) projects support various aspects of power system operations. However, determining the value of PSH projects and the many services and contributions to the system they provide can be a challenge. The PSH techno-economic studies being carried out by a 5-lab consortium are defining extensive modeling approaches for evaluating the economic benefits of PSH projects. To enhance the impact of the valuation approach and follow-on techno-economic studies, Pacific Northwest National Laboratory (PNNL) will be developing a set of online tools that industry could adopt and use to advance PSH projects in the US. The problem is that the research team is not entirely clear on the features of the tools that would offer the most significant impact to industry. Thus, year one of this effort is designed to first define the needs of industry before developing the PSH valuation tool. The first step in defining industry needs is to evaluate existing tool packages, including those created by DOE and those by industry groups, to both measure usage levels and define tool attributes that maximize industry impact. The second step in this process will be to hold a workshop designed to elicit direct industry input. Given the breadth and nature of the task, which is to define ideal model attributes, the research team did not constrain the assessment to storage valuation tools. Several tools were assessed, and their characteristics compared against a list of “ideal” attributes that included ease of use, generalizability of results, and analytical flexibility. Information regarding usage and impact were then compared to specific model attributes to define which attributes appear to drive success. The following key lessons and implications can be drawn from the analysis: Models with high ease of use were often the most adopted by industry, though they did not necessarily have high publication reference records, meaning a published article made direct reference to the tool. For example, REScheck TM and COMcheck TM , two tools which share a site, have seen a high amount of web traffic and usage. Similarly, Storage Value Estimate Tool (StorageVET®), an energy storage valuation model, has a large number of organizations using it despite a low publication reference record. A common feature between these models is that they are web-hosted, theoretically making them more easily accessible with graphic user interfaces (GUIs) that are more navigable; Models with higher usage statistics were typically free and/or open source. While it may be unsurprising that this attribute could be considered a draw for users, there is the potential for overestimating the tool's value based on popularity due to the fact that some users may have used the model simply because it was free and not because it is the best model; Models that offer more in-depth analysis and a wide coverage of applications (e.g. VOLTTRON™, GridLAB-D™, and Integrated Valuation of Ecosystem Services and Tradeoffs (InVest)) have shown a high number of publication references as well as showing a high number of downloads in the case of GridLAB-D™. It should be noted that the figure below does not include the model with the highest number of publication references (EnergyPlus™) as it has been removed to show clearer distinction between the remaining tools; The most popular model within the evaluation list was EnergyPlus™. This tool has the highest number of publication references (2,034) of all models considered and contains both a high ease of use level as well as broad application flexibility. Its high usage may be correlated, however, with the presumed wider audience conducting energy consumption modeling compared to the audiences for some of the other tools in this list; Models that were low in both general usage and publication reference generally did not exhibit characteristics considered ideal by the research team. Some of these models offered a narrower range of analytical applications or lower generalizability of results. This would automatically restrict the pool of potential users to those who fall within a narrow range of specific technologies or applications. This report also explores two model structures for the PSH tool: decision tree-based, which would guide the user through the valuation methods defined in the PSH techno-economic studies currently being carried out by DOE, and an all-inclusive comprehensive model. The strengths of each were explored and a hybrid approach was defined that would embed a price taker model into the decision tree approach. Such an approach would provide a comprehensive approach for modeling small-scale PSH while recognizing the challenges associated with implementing a price-maker approach in an all-inclusive model. Insight gained in this analysis of other models can aid in narrowing down the list of effective and sought-after attributes, and in defining model structure. Next steps toward developing a model for storage valuation will be to gain direct industry input through workshops.

13 HYDRO ENERGY↗
DOE OSTI2016

Analytic study of the effect of dark energy-dark matter interaction on the growth of structures

Large-scale structure has been shown as a promising cosmic probe for distinguishing and constraining dark energy models. Using the growth index parametrization, we obtain an analytic formula for the growth rate of structures in a coupled dark energy model in which the exchange of energy-momentum is proportional to the dark energy density. We find that the evolution of f σ{sub 8} can be determined analytically once we know the coupling, the dark energy equation of state, the present value of the dark energy density parameter and the current mean amplitude of dark matter fluctuations. After correcting the growth function for the correspondence with the velocity field through the continuity equation in the interacting model, we use our analytic result to compare the model's predictions with large-scale structure observations.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2016

Comparing Potential Recharge Estimates From Three Land Surface Models Across the Western US

Groundwater is a major source of water in the western US. However, there are limited recharge estimates available in this region due to the complexity of recharge processes and the challenge of direct observations. Land surface Models (LSMs) could be a valuable tool for estimating current recharge and projecting changes due to future climate change. In this study, simulations of three LSMs (Noah, Mosaic and VIC) obtained from the North American Land Data Assimilation System (NLDAS-2) are used to estimate potential recharge in the western US Modeled recharge was compared with published recharge estimates for several aquifers in the region. Annual recharge to precipitation ratios across the study basins varied from 0.01-15% for Mosaic, 3.2-42% for Noah, and 6.7-31.8% for VIC simulations. Mosaic consistently underestimates recharge across all basins. Noah captures recharge reasonably well in wetter basins, but overestimates it in drier basins. VIC slightly overestimates recharge in drier basins and slightly underestimates it for wetter basins. While the average annual recharge values vary among the models, the models were consistent in identifying high and low recharge areas in the region. Models agree in seasonality of recharge occurring dominantly during the spring across the region. Overall, our results highlight that LSMs have the potential to capture the spatial and temporal patterns as well as seasonality of recharge at large scales. Therefore, LSMs (specifically VIC and Noah) can be used as a tool for estimating future recharge rates in data limited regions.

groundwater↗
DOE OSTI2019

The reconstructed power spectrum in the Zeldovich approximation

Density-reconstruction sharpens the baryon acoustic oscillations signal by undoing some of the smoothing incurred by nonlinear structure formation. Here, we present an analytical model for reconstruction based on the Zeldovich approximation, which for the first time includes a complete set of counterterms and bias terms up to quadratic order and can fit real and redshift-space data pre- and post-reconstruction data in both Fourier and configuration space over a wide range of scales. We compare our model to n-body data at $z = 0$ from the ${\tt DarkSky}$ simulation, finding sub-percent agreement in both real space and in the redshift-space power spectrum monopole out to $k = 0.4\ h$ Mpc$^{-1}$, and out to $k = 0.2\ h$ Mpc$^{-1}$ in the quadrupole, with comparable agreement in configuration space. We compare our model with several popular existing alternatives, updating existing theoretical findings for exponential damping in wiggle/no-wiggle splits of the BAO signal and discuss the usually-ignored effect of higher bias contributions on the reconstructed signal. In the appendices, we re-derive the former within our formalism, present exploratory results on higher-order corrections due to nonlinearities inherent to reconstruction, and present numerical techniques with which to calculate the redshift-space power spectrum of biased tracers within the Zeldovich approximation.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Comparing event generator predictions and ab-initio calculations of $\nu$-$^{12}$C neutral current quasi-elastic scattering at 1 GeV

The measurement of neutrino oscillations and exotic physics searches are important parts of the physics program in the near future, with new state-of-the-art experiments planned within the next decade. Future and modern experiments in these fields will make use of nuclear targets. Event Generators (EGs) are software used in the analysis of neutrino oscillation experiments. EGs use to predict kinematic observables for a range of neutrino energies. These simulations may lack physics captured by more rigorous theoretical calculations. This work compares EG performance to nuclear theory calculations by comparing observables generated in the two frameworks. We provide a common set of definitions between theory and experiment and assess the physics contained in EG simulations. Neutral current quasi-elastic (NCQE) scattering events for neutrinos and anti-neutrinos on a $^{12}$C target are simulated with a specific EG, NEUT, used by the T2K experiment for its analysis. The simulated cross sections are compared to analytic calculations from nuclear theory within the factorization scheme. We compare the NEUT implementation of two different models on nuclear spectral functions: the Relativistic Fermi Gas (RFG) and the correlated basis spectral function (CBF) to analytic calculations of the same models in the factorization scheme. For both nuclear physics models, we compare the appearance of features in the distributions relevant to experimental analyses. Qualitatively, the shape of the simulated distribution is similar to the one obtained through theory calculations; however, there are some discrepancies between the theory calculations and the NEUT simulation. While the EG simulations and analytic calculations with the same model of nuclear dynamics show similar overall features, there are still differences between the two.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗