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At least 775 records · Page 43
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Final Technical Report for Interagency Agreement No. DE-SC0005453 “Characterizing Aerosol Distributions, Types, and Optical and Microphysical Properties using the NASA Airborne High Spectral Resolution Lidar (HSRL) and the Research Scanning Polarimeter (RSP)”

Measurements of the vertical profile of atmospheric aerosols and aerosol optical and microphysical characteristics are required to: 1) determine aerosol direct and indirect radiative forcing, 2) compute radiative flux and heating rate profiles, 3) assess model simulations of aerosol distributions and types, and 4) establish the ability of surface and space-based remote sensors to measure the indirect effect. Consequently the ASR program calls for a combination of remote sensing and in situ measurements to determine aerosol properties and aerosol influences on clouds and radiation. As part of our previous DOE ASP project, we deployed the NASA Langley airborne High Spectral Resolution Lidar (HSRL) on the NASA B200 King Air aircraft during major field experiments in 2006 (MILAGRO and MaxTEX), 2007 (CHAPS), 2009 (RACORO), and 2010 (CalNex and CARES). The HSRL provided measurements of aerosol extinction (532 nm), backscatter (532 and 1064 nm), and depolarization (532 and 1064 nm). These measurements were typically made in close temporal and spatial coincidence with measurements made from DOE-funded and other participating aircraft and ground sites. On the RACORO, CARES, and CalNEX missions, we also deployed the NASA Goddard Institute for Space Studies (GISS) Research Scanning Polarimeter (RSP). RSP provided intensity and degree of linear polarization over a broad spectral and angular range enabling column-average retrievals of aerosol optical and microphysical properties. Under this project, we analyzed observations and model results from RACORO, CARES, and CalNex and accomplished the following objectives. 1. Identified aerosol types, characterize the vertical distribution of the aerosol types, and partition aerosol optical depth by type, for CARES and CalNex using HSRL data as we have done for previous missions. 2. Investigated aerosol microphysical and macrophysical properties using the RSP. 3. Used the aerosol backscatter and extinction profiles measured by the HSRL to characterize the planetary boundary layer height (PBL) and the transition zone thickness, for the RACORO and CARES and CalNex campaigns as we have done for previous campaigns. 4. Investigated how optical properties measured by HSRL vary near clouds. 5. Assessed model simulations of aerosol spatial distributions and optical and microphysical properties.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Predicting Emission Source Terms in a Reduced-Order Fire Spread Model—Part 1: Particulate Emissions

A simple, easy-to-evaluate, surrogate model was developed for predicting the particle emission source term in wildfire simulations. In creating this model, we conceptualized wildfire as a series of flamelets, and using this concept of flamelets, we developed a one-dimensional model to represent the structure of these flamelets which then could be used to simulate the evolution of a single flamelet. A previously developed soot model was executed within this flamelet simulation which could produce a particle size distribution. Executing this flamelet simulation 1200 times with varying conditions created a data set of emitted particle size distributions to which simple rational equations could be tuned to predict a particle emission factor, mean particle size, and standard deviation of particle sizes. These surrogate models (the rational equation) were implemented into a reduced-order fire spread model, QUIC-Fire. Using QUIC-Fire, an ensemble of simulations were executed for grassland fires, southeast U.S. conifer forests, and western mountain conifer forests. Resulting emission factors from this ensemble were compared against field data for these fire classes with promising results. Also shown is a predicted averaged resulting particle size distribution with the bulk of particles produced to be on the order of 1 μm in size.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2010

Radiation of a circulating quark in strongly coupled N = 4 super Yang-Mills theory

The energy density and angular distribution of power radiated by a quark undergoing circular motion in strongly coupled N = 4 supersymmetric Yang-Mills (SYM) theory is computed using gauge/gravity duality. The results are qualitatively similar to that of synchrotron radiation produced by an electron in circular motion in classical electrodynamics: At large velocities the quark emits radiation in a narrow beam along its velocity vector with a characteristic opening angle {alpha}{approx}1/{gamma} and radial thickness scaling like {approx}1/{gamma}{sup 3}.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2011

Elastic {sup 16}O+{sup 20}Ne scattering from a folding model analysis

A folding potential for elastic {sup 16}O+{sup 20}Ne scattering is constructed based on the four-{alpha}-particle model for the {sup 16}O nucleus and the {alpha}+{sup 16}O model for the {sup 20}Ne nucleus. The elastic scattering angular distributions of the {sup 16}O+{sup 20}Ne system in the energy range of E{sub c.m.}=24.5-35.5 MeV are calculated by use of the {alpha}-folding potential obtained. The calculations show that the experimental data can be reasonably well described. The surface term in the imaginary potential has a significant effect on the calculations of the cross section at large angles for the energies considered.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2013

Integrated Simulation Development and Decision Support Tool-Set for Utility Market and Distributed Solar Power Generation

This project will enable utilities to develop long-term strategic plans that integrate high levels of renewable energy generation, and to better plan power system operations under high renewable penetration. The program developed forecast data streams for decision support and effective integration of centralized and distributed solar power generation in utility operations. This toolset focused on real time simulation of distributed power generation within utility grids with the emphasis on potential applications in day ahead (market) and real time (reliability) utility operations. The project team developed and demonstrated methodologies for quantifying the impact of distributed solar generation on core utility operations, identified protocols for internal data communication requirements, and worked with utility personnel to adapt the new distributed generation (DG) forecasts seamlessly within existing Load and Generation procedures through a sophisticated DMS. This project supported the objectives of the SunShot Initiative and SUNRISE by enabling core utility operations to enhance their simulation capability to analyze and prepare for the impacts of high penetrations of solar on the power grid. The impact of high penetration solar PV on utility operations is not only limited to control centers, but across many core operations. Benefits of an enhanced DMS using state-of-the-art solar forecast data were demonstrated within this project and have had an immediate direct operational cost savings for Energy Marketing for Day Ahead generation commitments, Real Time Operations, Load Forecasting (at an aggregate system level for Day Ahead), Demand Response, Long term Planning (asset management), Distribution Operations, and core ancillary services as required for balancing and reliability. This provided power system operators with the necessary tools and processes to operate the grid in a reliable manner under high renewable penetration.

14 SOLAR ENERGY↗
DOE OSTI2014

Final Technical Report for Contract No. DE-EE0006332, "Integrated Simulation Development and Decision Support Tool-Set for Utility Market and Distributed Solar Power Generation"

This project will enable utilities to develop long-term strategic plans that integrate high levels of renewable energy generation, and to better plan power system operations under high renewable penetration. The program developed forecast data streams for decision support and effective integration of centralized and distributed solar power generation in utility operations. This toolset focused on real time simulation of distributed power generation within utility grids with the emphasis on potential applications in day ahead (market) and real time (reliability) utility operations. The project team developed and demonstrated methodologies for quantifying the impact of distributed solar generation on core utility operations, identified protocols for internal data communication requirements, and worked with utility personnel to adapt the new distributed generation (DG) forecasts seamlessly within existing Load and Generation procedures through a sophisticated DMS. This project supported the objectives of the SunShot Initiative and SUNRISE by enabling core utility operations to enhance their simulation capability to analyze and prepare for the impacts of high penetrations of solar on the power grid. The impact of high penetration solar PV on utility operations is not only limited to control centers, but across many core operations. Benefits of an enhanced DMS using state-of-the-art solar forecast data were demonstrated within this project and have had an immediate direct operational cost savings for Energy Marketing for Day Ahead generation commitments, Real Time Operations, Load Forecasting (at an aggregate system level for Day Ahead), Demand Response, Long term Planning (asset management), Distribution Operations, and core ancillary services as required for balancing and reliability. This provided power system operators with the necessary tools and processes to operate the grid in a reliable manner under high renewable penetration.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2012

Maximum Photovoltaic Penetration Levels on Typical Distribution Feeders: Preprint

This paper presents simulation results for a taxonomy of typical distribution feeders with various levels of photovoltaic (PV) penetration. For each of the 16 feeders simulated, the maximum PV penetration that did not result in steady-state voltage or current violation is presented for several PV location scenarios: clustered near the feeder source, clustered near the midpoint of the feeder,clustered near the end of the feeder, randomly located, and evenly distributed. In addition, the maximum level of PV is presented for single, large PV systems at each location. Maximum PV penetration was determined by requiring that feeder voltages stay within ANSI Range A and that feeder currents stay within the ranges determined by overcurrent protection devices. Simulations were run inGridLAB-D using hourly time steps over a year with randomized load profiles based on utility data and typical meteorological year weather data. For 86% of the cases simulated, maximum PV penetration was at least 30% of peak load.

14 SOLAR ENERGY↗
DOE OSTI2011

Building A Simulation Model For The Prediction Of Temperature Distribution In Pulsed Laser Spot Welding Of Dissimilar Low Carbon Steel 1020 To Aluminum Alloy 6061

This paper describes the development of a computer model used to analyze the heat flow during pulsed Nd: YAG laser spot welding of dissimilar metal; low carbon steel (1020) to aluminum alloy (6061). The model is built using ANSYS FLUENT 3.6 software where almost all the environments simulated to be similar to the experimental environments. A simulation analysis was implemented based on conduction heat transfer out of the key hole where no melting occurs. The effect of laser power and pulse duration was studied.Three peak powers 1, 1.66 and 2.5 kW were varied during pulsed laser spot welding (keeping the energy constant), also the effect of two pulse durations 4 and 8 ms (with constant peak power), on the transient temperature distribution and weld pool dimension were predicated using the present simulation. It was found that the present simulation model can give an indication for choosing the suitable laser parameters (i.e. pulse durations, peak power and interaction time required) during pulsed laser spot welding of dissimilar metals.

36 MATERIALS SCIENCE↗
DOE OSTI2014

Oxygen distribution in tumors: A qualitative analysis and modeling study providing a novel Monte Carlo approach

Purpose: To construct a Monte Carlo (MC)-based simulation model for analyzing the dependence of tumor oxygen distribution on different variables related to tumor vasculature [blood velocity, vessel-to-vessel proximity (vessel proximity), and inflowing oxygen partial pressure (pO{sub 2})]. Methods: A voxel-based tissue model containing parallel capillaries with square cross-sections (sides of 10 μm) was constructed. Green's function was used for diffusion calculations and Michaelis-Menten's kinetics to manage oxygen consumption. The model was tuned to approximately reproduce the oxygenational status of a renal carcinoma; the depth oxygenation curves (DOC) were fitted with an analytical expression to facilitate rapid MC simulations of tumor oxygen distribution. DOCs were simulated with three variables at three settings each (blood velocity, vessel proximity, and inflowing pO{sub 2}), which resulted in 27 combinations of conditions. To create a model that simulated variable oxygen distributions, the oxygen tension at a specific point was randomly sampled with trilinear interpolation in the dataset from the first simulation. Six correlations between blood velocity, vessel proximity, and inflowing pO{sub 2} were hypothesized. Variable models with correlated parameters were compared to each other and to a nonvariable, DOC-based model to evaluate the differences in simulated oxygen distributions and tumor radiosensitivities for different tumor sizes. Results: For tumors with radii ranging from 5 to 30 mm, the nonvariable DOC model tended to generate normal or log-normal oxygen distributions, with a cut-off at zero. The pO{sub 2} distributions simulated with the six-variable DOC models were quite different from the distributions generated with the nonvariable DOC model; in the former case the variable models simulated oxygen distributions that were more similar to in vivo results found in the literature. For larger tumors, the oxygen distributions became truncated in the lower end, due to anoxia, but smaller tumors showed undisturbed oxygen distributions. The six different models with correlated parameters generated three classes of oxygen distributions. The first was a hypothetical, negative covariance between vessel proximity and pO{sub 2} (VPO-C scenario); the second was a hypothetical positive covariance between vessel proximity and pO{sub 2} (VPO+C scenario); and the third was the hypothesis of no correlation between vessel proximity and pO{sub 2} (UP scenario). The VPO-C scenario produced a distinctly different oxygen distribution than the two other scenarios. The shape of the VPO-C scenario was similar to that of the nonvariable DOC model, and the larger the tumor, the greater the similarity between the two models. For all simulations, the mean oxygen tension decreased and the hypoxic fraction increased with tumor size. The absorbed dose required for definitive tumor control was highest for the VPO+C scenario, followed by the UP and VPO-C scenarios. Conclusions: A novel MC algorithm was presented which simulated oxygen distributions and radiation response for various biological parameter values. The analysis showed that the VPO-C scenario generated a clearly different oxygen distribution from the VPO+C scenario; the former exhibited a lower hypoxic fraction and higher radiosensitivity. In future studies, this modeling approach might be valuable for qualitative analyses of factors that affect oxygen distribution as well as analyses of specific experimental and clinical situations.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2019

Using Willingness to Pay to Forecast the Adoption of Solar Photovoltaics: A ''Parameterization + Calibration'' Approach

Distributed energy resources, such as rooftop solar photovoltaics (PV), are likely to comprise a substantial fraction of new generation capacity in the United States. However, forecasting technology adoption based on people's willingness to pay (WTP) faces two major challenges: the stated-intention and omitted-variable biases. Previous solar adoption literature has neglected to address these two biases altogether. Here, we adopt a 'parameterization + calibration' approach to address both biases and estimate customers' WTP for PV. After collecting survey data on respondents' WTP for adopting PV, we characterize its empirical cumulative density function using a gamma distribution. We further calibrate the gamma distribution parameters using a national distributed PV adoption simulation model, finding the parameters that produce the best fit between simulated and historic solar adoption. We then show that the calibrated gamma distribution improves the raw WTP data after correcting for the two biases. Finally, we use our optimally-calibrated WTP to forecast market demand for residential PV at the county-level of the United States in 2020. Improving estimates of customer willingness to pay has significant implications for policy directly, e.g. estimating the effect of a proposed policy on technology adoption, and other regulatory processes that use forecasting, e.g. integrated resource planning.

14 SOLAR ENERGY↗
DOE OSTI2017

Toward Personalized Dosimetry with {sup 32}P Microparticle Therapy for Advanced Pancreatic Cancer

Purpose: To develop a Monte Carlo model for patient-specific dosimetry of {sup 32}P microparticle localized internal radionuclide therapy for advanced pancreatic cancer. Methods and Materials: Spherical tumor geometries and a pancreatic phantom were modeled, as well as different 3-dimensional non-uniform clinical pancreatic geometries based on patient-specific ultrasound images. The dosimetry simulations modeled the dose distribution due to the energy spectrum of emitted beta particles. Results: The average dose for small (3-cm diameter) and large (6-cm diameter) spherical tumors was 111 Gy (for 7.6 MBq administered activity) and 128 Gy (for 58 MBq), respectively. For the clinical 3-dimensional geometries, on the basis of patient data, the mean doses delivered to the tumor were calculated to be in the range 102 to 113 Gy, with negligible dose to the pancreas for the smallest tumor volumes. The calculated dose distributions are highly non-uniform. For the largest tumor studied, the pancreas received approximately 6% of the tumor dose (5.7 Gy). Importantly, we found that because the smallest tumor studied exhibited the most dynamic changes in volume in response to the treatment, the dose to tumor and pancreas is significantly underestimated if a static tumor volume is assumed. Conclusions: These results demonstrate the dosimetry of {sup 32}P microparticle localized internal radionuclide therapy for pancreatic cancer and the possibility of developing personalized treatment strategies. The results also highlight the importance of considering the effects of non-uniform dose distributions and dynamic change of tumor mass during treatment on the dosimetry of the tumor and critical organs.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2014

Distribution of CCS and HC{sub 3}N in L1147, an early phase dark cloud

We used the Nobeyama 45 m radio telescope to reveal spatial distributions of CCS and HC{sub 3}N in L1147, one of the carbon-chain producing region (CCPR) candidates, where carbon-chain molecules are dominant rather than NH{sub 3}. We found that three cores (two CCS cores and one HC{sub 3}N core), which are away from a very low luminosity object (a source that may turn into a sub-stellar mass brown dwarf), exist along the NE-SW filament traced by the 850 μm dust continuum. The column densities of CCS are 3-7 × 10{sup 12} cm{sup –2} and those of HC{sub 3}N are 2-6 × 10{sup 12} cm{sup –2}, respectively, much lower than those previously reported toward other CCPRs. We also found that two CCS peaks are displaced from the peaks of HC{sub 3}N. In order to interpret such interleaved distributions, we conducted chemical reaction network simulations and found that slightly different gas densities could lead to large variation of the CCS-to-HC{sub 3}N ratio in the early phase of dark cloud evolution. Such a chemical 'variation' may be seen in other CCPRs. Finally, we were able to confirm that the L1147 filament can be regarded as a CCPR.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2012

Using spatial information about recurrence risk for robust optimization of dose-painting prescription functions

Purpose: To develop a robust method for deriving dose-painting prescription functions using spatial information about the risk for disease recurrence. Methods: Spatial distributions of radiobiological model parameters are derived from distributions of recurrence risk after uniform irradiation. These model parameters are then used to derive optimal dose-painting prescription functions given a constant mean biologically effective dose. Results: An estimate for the optimal dose distribution can be derived based on spatial information about recurrence risk. Dose painting based on imaging markers that are moderately or poorly correlated with recurrence risk are predicted to potentially result in inferior disease control when compared the same mean biologically effective dose delivered uniformly. A robust optimization approach may partially mitigate this issue. Conclusions: The methods described here can be used to derive an estimate for a robust, patient-specific prescription function for use in dose painting. Two approximate scaling relationships were observed: First, the optimal choice for the maximum dose differential when using either a linear or two-compartment prescription function is proportional to R, where R is the Pearson correlation coefficient between a given imaging marker and recurrence risk after uniform irradiation. Second, the predicted maximum possible gain in tumor control probability for any robust optimization technique is nearly proportional to the square of R.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2015

A method for modeling laterally asymmetric proton beamlets resulting from collimation

Purpose: To introduce a method to model the 3D dose distribution of laterally asymmetric proton beamlets resulting from collimation. The model enables rapid beamlet calculation for spot scanning (SS) delivery using a novel penumbra-reducing dynamic collimation system (DCS) with two pairs of trimmers oriented perpendicular to each other. Methods: Trimmed beamlet dose distributions in water were simulated with MCNPX and the collimating effects noted in the simulations were validated by experimental measurement. The simulated beamlets were modeled analytically using integral depth dose curves along with an asymmetric Gaussian function to represent fluence in the beam’s eye view (BEV). The BEV parameters consisted of Gaussian standard deviations (sigmas) along each primary axis (σ{sub x1},σ{sub x2},σ{sub y1},σ{sub y2}) together with the spatial location of the maximum dose (μ{sub x},μ{sub y}). Percent depth dose variation with trimmer position was accounted for with a depth-dependent correction function. Beamlet growth with depth was accounted for by combining the in-air divergence with Hong’s fit of the Highland approximation along each axis in the BEV. Results: The beamlet model showed excellent agreement with the Monte Carlo simulation data used as a benchmark. The overall passing rate for a 3D gamma test with 3%/3 mm passing criteria was 96.1% between the analytical model and Monte Carlo data in an example treatment plan. Conclusions: The analytical model is capable of accurately representing individual asymmetric beamlets resulting from use of the DCS. This method enables integration of the DCS into a treatment planning system to perform dose computation in patient datasets. The method could be generalized for use with any SS collimation system in which blades, leaves, or trimmers are used to laterally sharpen beamlets.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2020

Distributed Generation Market Demand (dGen) model

The Distributed Generation Market Demand (dGen) model simulates customer adoption of distributed energy resources (DERs) for residential, commercial, and industrial entities in the United States or other countries through 2050. The dGen model can be used for identifying the sectors, locations, and customers for whom adopting DERs would have a high economic value, for generating forecasts as an input to estimate distribution hosting capacity analysis, integrated resource planning, and load forecasting, and for understanding the economic or policy conditions in which DER adoption becomes viable, and for illustrating sensitivity to market and policy changes such as retail electricity rate structures, net energy metering, and technology costs.

Array↗
DOE OSTI2016

Being WISE II: reducing the influence of star formation history on the mass-to-light ratio of quiescent galaxies

Stellar population synthesis models can now reproduce the photometry of old stellar systems (age > 2 Gyr) in the near-infrared (NIR) bands at 3.4 and 4.6 μm (WISE W1 and W2 or IRAC 1 and 2). In this paper, we derive stellar mass-to-light ratios for these and optical bands, and confirm that the NIR M/L shows dramatically reduced sensitivity to both age and metallicity compared to optical bands, and further, that this behavior leads to significantly more robust stellar masses for quiescent galaxies with [Fe/H] ≳ −0.5 regardless of star-formation history (SFH). We then use realistic early-type galaxy SFHs and metallicity distributions from the EAGLE simulations of galaxy formation to investigate two methods to determine the appropriate M/L for a galaxy. (1) We show that the uncertainties introduced by an unknown SFH can be largely removed using a spectroscopically inferred luminosity-weighted age and metallicity for the population to select the appropriate single stellar population (SSP) equivalent M/L. Using this method, the maximum systematic error due to SFH on the M/L of an early-type galaxy is <4% at 3.4 μm and typical uncertainties due to errors in the age and metallicity create a scatter of ≲13%. The equivalent values for optical bands are more than two to three times greater, even before considering uncertainties associated with internal dust extinction. (2) We demonstrate that if the EAGLE SFHs and metallicities accurately reproduce the true properties of early-type galaxies, the use of an iterative approach to select a mass dependent M/L can provide even more accurate stellar masses for early-type galaxies, with typical uncertainties of <9%.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

Powered by dGen Webinar [Slides]

NLR's Powered By Webinar Series featuring NLR's dGen Modeling Tool. The Distributed Generation Market Demand (dGenTM) model simulates customer adoption of distributed energy resources for residential, commercial, and industrial entities in the United States or other countries through 2050. The model enables analysis at multiple geographic levels (national, state, and utility, or below) and offers sophistication in representation of decision-making regarding economic and behavioral considerations. Analysts have used dGen to answer questions about load forecasting and integrated resource planning, policy analysis, locational value of distributed energy resources, and more. dGen is open source, and various energy organizations - including independent system operators, regional transmission organizations, and the California Energy Commission - use the model internally.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗