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At least 1,045 records · Page 58
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Description of the multinucleon transfer mechanism for Ca 48 + Pu 244 and Kr 86 + Pt 198 reactions in a quantal transport approach

Multinucleon transfer (MNT) reactions involving heavy projectile and target combinations stand as a promising method for synthesizing new neutron-rich exotic nuclei, which may not be possible using hot or cold fusion reactions or fragmentation. Exploring the mechanisms behind MNT reactions is essential and it requires a comprehensive theoretical framework that can explain the physical observables in these reactions. This work aims to show that the quantal diffusion approach based on the stochastic mean-field (SMF) theory is capable of explaining the reaction dynamics observed in MNT reactions. Primary product mass distributions in 48 Ca + 244 Pu reaction at E c.m. = 203.2 MeV and 86 Kr + 198 Pt reaction at E c.m. = 324.2 MeV are calculated and compared with the available experimental data. In this work, we utilize the time-dependent Hartree-Fock (TDHF) calculations to analyze the mean-field reaction dynamics computationally in the reactions 48 Ca + 244 Pu and 86 Kr + 198 Pt for a broad range of initial angular momenta. Quantal transport description based on the SMF approach is used to calculate quantal diffusion coefficients and mass variances in 48 Ca + 244 Pu and 86 Kr + 198 Pt systems. The primary products arising from quasifission reactions are described by joint probability distribution in the SMF approach and those arising from fusion-fission are estimated by using the statistical deexcitation code gemini + +. Mean values of charge and mass numbers, scattering angles of the primary reaction products, and the total kinetic energies after the collision are calculated within the TDHF framework for a broad range of initial angular momenta. Throughout all the collisions, drift toward the mass symmetry and large mass dispersion associated with this drift are observed. Here, the calculated primary fragment and mass distributions using the SMF approach successfully explain experimental observations for the 48 Ca + 244 Pu and 86 Kr + 198 Pt systems. The primary mass distributions, mean values of binary products, and mass dispersions are determined and results are compared with the available experimental data. The observed agreement between the experimental data and SMF results highlights the effectiveness of the quantal diffusion mechanism based on the SMF approach, which does not include any adjustable parameters other than standard parameters of Skyrme energy density functional.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2019

Quantifying Resolution Implications for Agent-based Distributed Energy Resource Customer Adoption Models

In this report we explore tradeoffs of top-down and bottom-up methods in their precision and computational burden using NREL's dGen model, an agent-based model of residential and non-residential distributed PV adoption. In particular, we assess the role of agent resolution in instantiating statistically-representative populations in the model--and the resulting variance of model projections at the state, sector and county levels. Running the model for a single state with fixed macroeconomic assumptions, we vary both the number of agents instantiated and the number of unique simulations. Notably, in each run we introduce sources of uncertainty in cumulative DPV adoption results during agent instantiation as we stochastically sample agent attributes from localized building characteristic and solar resource distributions. We find three key trends which guide what can be expected of results. First, precision of the model projections, as measured by the variance of the unique simulations increased as a function of the number of agents sampled, though with diminishing returns to scale. The result is expected given the Law of Large Numbers. Second, the mean or expected value of projections decreased as the number of agents instantiated increased. Empirically, aggregate DPV capacities projected by dGen are 7% lower on average at a 10-agent resolution compared to 1-agent resolutions, and up to 10% lower in the non-residential sector. We attribute this outcome to a system sizing scheme that biases lower cumulative installed capacity as agent resolution increases when roof size and load are not positively correlated. Finally, the variance of model projections differed by sector, where variance was substantially larger in the commercial sector, largely due to differences in parameterization by sector. We explain the larger variance in the non-residential sector as an outcome of the greater variance in building uses and load shapes as compared to the residential sector, and we find that a resolution on the order of 100-agents per county would be necessary to bring non-residential variance in line with residential variance at a 2-agent resolution. We propose that further research explore increasing precision and agent resolution in the non-residential sector. Moreover, given that days of intensive computing may be required to resolve a suitable estimate even at the extent of a single state within acceptable levels of precision, to promote computational efficiency we also suggest more clearly quantifying sources of variability at the county level such that resolution can by dynamically increased where county level results are least precise.

14 SOLAR ENERGY↗
DOE OSTI2023

Implementation and Performance Evaluation of a Community-Scale Adobe Evaporative Cooling Chamber for Vegetable Preservation

The construction of evaporative coolers in remote areas can increase the longevity of vegetables, improving food security and the local economy of small farmers in remote, impoverished communities without access to electricity. This work presents a 1:1 scale prototype of an 8 m 3 (2.1 × 2.1 × 2.3 m) stabilized adobe evaporative cooler, with a design based on the appropriate technology framework, and it was built as a chamber using double adobe walls, filled with wet sand, to induce evaporative cooling. Furthermore, the paper presents the prototype’s performance evaluation. The tests were carried out in the dry and wet states, with different volumes of water. The results show good performance compared with other prototypes, although the optimum watering volume could not be determined because of the high climate variance (outside temperature and humidity) that prevented the repetition of the experiments in identical operating conditions. Stabilized adobe proved to be a good choice for use in the cooler, even when subject to moisture accumulation, indicating an estimated long lifetime for the cooler. The data obtained about the efficiency of evaporative cooling show that the cooler, as expected, has its best performance on the hottest and driest days, reducing the internal temperature (up to 13.24 °C) and managing to keep the internal humidity. The cost, efficiency, durability, and replicability make the proposed evaporative cooler a feasible solution for food preservation.

42 ENGINEERING↗
NASA NTRS1973

Maximum likelihood synchronizer for binary overlapping PCM/NRZ signals.

A maximum likelihood parameter estimation technique for the self bit synchronization problem is investigated. The input sequence to the bit synchronizer is a sequence of binary overlapping PCM/NRZ signal in the presence of white Gaussian noise with zero mean and known variance. The resulting synchronizer consists of matched filters, a transition device and a weighting function. Finally, the performance is examined by Monte Carlo simulations.

Wang, C. D.↗
NASA NTRS1975

Mapping of the wildland fuel characteristics of the Santa Monica mountains of Southern California

LANDSAT digital data was successfully used to map and evaluate the wildland fuels of the Santa Monica Mountains in Southern California. A mixed classification scheme was used where training areas of known vegetation types were entered and the maximum likelihood classifier run, followed by an evaluation of the results and an unsupervised retraining of the classifier using an image of the probability of misclassification. Estimation of maturity class and crown closure percents of the major cover types were assigned to each computer class by associating the photointerpretation of 159 large scale photo samples with the resultant computer classes using analysis of variance and analysis of categorized data. The result of the computer classification and statistical analysis were then transformed from the LANDSAT Coordinate California State Plane Coordinate system for use in a digital format in the FIRESCOPE data retrieval and fire modeling system.

Nichols, J. D.↗
NASA NTRS1981

Structure of Jupiter's magnetopause - Pioneer 10 and 11 observations

The magnetic structure of Jupiter's magnetopause, as observed by the space probes Pioneer 10 and 11, is compared with terrestrial magnetopause structures from the OGO 5 mission. The Jovian magnetopause thickness, deduced from a rapid triple crossing, is found to lie in the range 3500-5200 km, while the adjoining plasma boundary layer was 5600-8400 km thick. Comparison with the terrestrial situation suggests that the dayside magnetopause thickness in both cases is a few times the ion gyroradius and that the dayside boundary layer is also of about the same width. The magnetopause normal vector and normal magnetic field component are determined for each crossing by use of minimum variance analysis. The results indicate a blunt and floppy magnetopause surface, for the most part with an insignificant normal magnetic field component. Only for three of the 14 crossings did this component exceed 1.5 times its error estimate. In two of these cases, the magnetic field tangential to the magnetopause displayed the characteristic features of a rotational discontinuity.

Sonnerup, B. U. O.↗
NASA NTRS1989

Seasonal variability in global sea level observed with Geosat altimetry

Time changes in global mesoscale sea level variances were observed with satellite altimetry between November 1986 and March 1988, showing significant, geographically coherent seasonal patterns. The NE Pacific and NE Atlantic variances show the most reliable patterns, higher than their yearly averages in both the fall and winter. The response to wind forcing appears as the major contributor to the NE Pacific and Atlantic signals; errors in the estimated inverse barometer response due to errors in atmospheric pressure, residual orbit errors, and errors in sea state bias are evaluated and found to be negligible contributors to this particular signal. The equatorial regions also show significant seasonal patterns, but the uncertainties in the wet tropospheric correction prevent definitive conclusions. The western boundary current changes are very large but not statistically significant. Estimates of the regression coefficient between sea level and significant wave height, an estimate of the sea state bias correction, range between 2.3 and 2.9 percent and vary with the type of orbit correction applied.

Zlotnicki, V.↗
NASA NTRS1992

A second-order bulk boundary-layer model

Bulk mass-flux models represent the large eddies that are primarily responsible for the turbulent fluxes in the planetary boundary layer as convective circulations, with an associated convective mass flux. In order for such models to be useful, it is necessary to determine the fractional area covered by rising motion in the convective circulations. This fraction can be used as an estimate of the cloud amount, under certain conditions. 'Matching' conditions have been developed that relate the convective mass flux to the ventilation and entrainment mass fluxes. These are based on conservation equations for the scalar means and variances in the entrainment and ventilation layers. Methods are presented to determine both the fractional area covered by rising motion and the convective mass flux. The requirement of variance balance is used to relax the 'well-mixed' assumption. The vertical structures of the mean state and the turbulent fluxes are determined analytically. Several aspects of this simple model's formulation are evaluated using results from large-eddy simulations.

Randall, David A.↗
NASA NTRS1994

Mesoscale roughness of Venus

The global distribution of multi-kilometer (approx. 9 km) length scale 'roughness' (hereafter mesoscale roughness or MR) on Venus can be estimated from the Magellan global altimetry dataset (GxDR) and then compared with MR data derived for Earth from 5' ETOP5 data and for Mars (from USGS Mars DTM dataset). The mesoscale roughness parameter (MR) represents the RMS variance in meters of the actual planetary surface topography relative to the best fitting tangent plane defined on the basis of a 3x3 pixel sliding window. The best-fit plane was computed using a least-squares solution which minimizes delta H, the sum of the squares of the differences between the 9 local elevation values (H(sub i)), and the elevation of best-fit plane at the same grid location. Using the best-fit plane and delta H, we have computed the RMS 'roughness' var(delta R), where this parameter is always minimized on the basis of its calculation using least squares. We have called this 'ruggedness' parameter the Mesoscale Roughness (MR) because it is directly related to the high-frequency variance of topography after mesoscale slopes and tilts (i.e., for Venus, the baseline over which MR is computed (dx) is approx. 8.8 km and dx for Earth is approx. 9.3 km) are removed. As such, MR represents the degree to which a planetary surface is more rugged than approximately 10 km scale facets or tilts. It should not be confused with the radar 'RMS Roughness' parameter computed at 0.1 to 10 m length scales on the basis of the Magellan radar altimeter echo. We will use our MR parameter to investigate the global ruggedness properties of Venus as they relate to geological provinces and in comparison with the spatial pattern of MR for Earth and Mars.

Garvin, J. B.↗
NASA NTRS2001

Crustal Displacements Due to Continental Water Loading

The effects of long-wavelength (> 100 km), seasonal variability in continental water storage on vertical crustal motions are assessed. The modeled vertical displacements (delta-r(sub M)) have root-mean-square (RMS) values for 1994-1998 as large as 8 mm with ranges up to 30 mm, and are predominantly annual in character. Regional strains are on the order of 20 nanostrain for tilt and 5 nanostrain for horizontal deformation. We compare delta-r(sub M) with observed Global Positioning System (GPS) heights (delta-r(sub O)) (which include adjustments to remove estimated effects of atmospheric pressure and annual tidal and non-tidal ocean loading) for 147 globally distributed sites. When the delta-r(sub O) time series are adjusted by delta-r(sub M), their variances are reduced, on average, by an amount equal to the variance of the delta-r(sub M). Of the delta-r(sub O) time series exhibiting a strong annual signal, more than half are found to have an annual harmonic that is in phase and of comparable amplitude with the annual harmonic in the delta-r(sub M). The delta-r(sub M) time series exhibit long-period variations that could be mistaken for secular tectonic trends or post-glacial rebound when observed over a time span of a few years.

vanDam, T.↗
NASA NTRS2001

An Analysis of Simulated and Observed Global Mean Near-Surface Air Temperature Anomalies from 1979 to 1999: Trends and Attribution of Causes

The 1979 - 1999 response of the climate system to variations in solar spectral irradiance is estimated by comparing the global averaged surface temperature anomalies simulated by a 2D (two dimensional) energy balance climate model to observed temperature anomalies. We perform a multiple regression of southern oscillation index and the individual model responses to solar irradiance variations, stratospheric and tropospheric aerosol loading, stratospheric ozone trends, and greenhouse gases onto each of five near-surface temperature anomaly data sets. We estimate the observed difference in global mean near surface air temperature attributable to the solar irradiance difference between solar maximum and solar minimum to be between 0.06 and 0.11 K, and that 1.1 - 3.8% of the total variance in monthly mean near-surface air temperature data is attributable to nations in solar spectral irradiance. For the five temperature data sets used in our analysis, the trends in raw monthly mean temperature anomaly data have a large range, spanning a factor of 3 from 0.06 to 0.17 K/decade. However. our analysis suggests that trends in monthly temperature anomalies attributable to the combination of greenhouse gas, stratospheric ozone, and tropospheric sulfate aerosol variations are much more consistent among data sets, ranging from 0.16 to 0.24 K/decade. Our model results suggest that roughly half of the warming from greenhouse gases is cancelled by the cooling from changes in stratospheric ozone. Tropospheric sulfate aerosol loading in the present day atmospheric contributes significantly to the net radiative forcing of the present day climate system. However, because the change in magnitude and latitudinal distribution of tropospheric sulfate aerosol has been small over the past 20 years, the change in the direct radiative forcing attributable to changes in aerosol loading over this time is also small.

MacKay, R. M.↗
DOE OSTI2023

Modeled production, oxidation, and transport processes of wetland methane emissions in temperate, boreal, and Arctic regions

Abstract Wetlands are the largest natural source of methane (CH 4 ) to the atmosphere. The eddy covariance method provides robust measurements of net ecosystem exchange of CH 4 , but interpreting its spatiotemporal variations is challenging due to the co‐occurrence of CH 4 production, oxidation, and transport dynamics. Here, we estimate these three processes using a data‐model fusion approach across 25 wetlands in temperate, boreal, and Arctic regions. Our data‐constrained model—iPEACE—reasonably reproduced CH 4 emissions at 19 of the 25 sites with normalized root mean square error of 0.59, correlation coefficient of 0.82, and normalized standard deviation of 0.87. Among the three processes, CH 4 production appeared to be the most important process, followed by oxidation in explaining inter‐site variations in CH 4 emissions. Based on a sensitivity analysis, CH 4 emissions were generally more sensitive to decreased water table than to increased gross primary productivity or soil temperature. For periods with leaf area index (LAI) of ≥20% of its annual peak, plant‐mediated transport appeared to be the major pathway for CH 4 transport. Contributions from ebullition and diffusion were relatively high during low LAI (<20%) periods. The lag time between CH 4 production and CH 4 emissions tended to be short in fen sites (3 ± 2 days) and long in bog sites (13 ± 10 days). Based on a principal component analysis, we found that parameters for CH 4 production, plant‐mediated transport, and diffusion through water explained 77% of the variance in the parameters across the 19 sites, highlighting the importance of these parameters for predicting wetland CH 4 emissions across biomes. These processes and associated parameters for CH 4 emissions among and within the wetlands provide useful insights for interpreting observed net CH 4 fluxes, estimating sensitivities to biophysical variables, and modeling global CH 4 fluxes.

Ueyama, Masahito↗
DOE OSTI2022

Deep learning to estimate permeability using geophysical data

Time-lapse electrical resistivity tomography (ERT) is a popular geophysical method to estimate three-dimensional (3D) permeability fields from electrical potential difference measurements. Traditional inversion and data assimilation methods are used to ingest this ERT data into hydrogeophysical models to estimate permeability. Due to ill-posedness and the curse of dimensionality, existing inversion strategies provide poor estimates and low resolution of the 3D permeability field. Recent advances in deep learning provide us with powerful algorithms to overcome this challenge. This paper presents a deep learning (DL) framework to estimate the 3D subsurface permeability from time-lapse ERT data. To test the feasibility of the proposed framework, we train DL-enabled inverse models on simulation data. Each measurement in both synthetic and field data is standardized by removing the mean and scaling the time-series to unit variance. This pre-processing step is necessary to bring simulation data closer to field observations. Subsurface process models based on hydrogeophysics are used to generate this synthetic data. Training performed on limited simulation data resulted in the DL model over-fitting. An advanced data augmentation based on mixup is implemented to generate additional training samples to overcome this issue. This mixup technique creates weakly labeled (low-fidelity) samples from strongly labeled (high-fidelity) data. The weakly labeled training data is then used to develop DL-enabled inverse models and reduce over-fitting. As both time-lapse ERT (1133048 features/realization) and 3D permeability (585453 features/realization) data samples are from a high-dimensional space, principal component analysis (PCA) is employed to reduce dimensionality. Encoded ERT and encoded permeability are generated using the trained PCA estimators. A deep neural network is then trained to map the encoded ERT to encoded permeability. This mixup training and unsupervised learning allowed us to build a fast and reasonably accurate DL-based inverse model under limited simulation data. Results show that proposed weak supervised learning can capture salient spatial features in the 3D permeability field. Quantitatively, the average mean squared error (in terms of the natural log) on the strongly labeled training, validation, and test datasets is less than 0.5. The R 2 -score (global metric) is greater than 0.75, and the percent error in each cell (local metric) is less than 10%. Finally, an added benefit in terms of computational cost is that the proposed DL-based inverse model is at least O(10 4 ) times faster than running a forward model once it is trained. Data generation, DL model training, and hyperparameter tuning to identify optimal neural network architectures utilized high-performance computing resources while the DL inference is performed on a standard laptop. Approximately, O(10 5 ) processor hours are used for generating data and DL tuning and training. We acknowledge that the data generation and DL model development are expensive. But once a DL model is trained, it can be re-used for inversion rapidly for the given system, with set physics and domain. Note that traditional inversion may require multiple forward model simulations (e.g., in the order of 10 to 1000), which are very expensive. This computational savings ≈ O(10 5 ) – O(10 7 )) makes the proposed DL-based inverse model attractive for subsurface imaging and real-time ERT monitoring applications due to fast and yet reasonably accurate estimations of permeability field.

58 GEOSCIENCES↗
NASA NTRS1992

Optimal Estimation of Rain Rate Profiles from Single-Frequency Radar Echoes

The significant ambiguities inherent in the determination of a particular vertical rain intensity profile from a given time profile of radar echo powers measured by a downward-looking (spaceborne or airborne) radar at a single attenuating frequency are well-documented. Indeed, one already knows that by appropriately varying the parameters of the reflectivity-rain-rate (Z - R) and/or attenuation-rain-rate (k - R) relationships, one can produce several substantially different hypothetical rain rate profiles which would have the same radar power profile. Imposing the additional constraint that the path-averaged rain-rate be a given fixed number does reduce the ambiguities but falls far short of eliminating them. While we now know how to generate as many mutually ambiguous rain-rate profiles from a given profile of received radar reflectivities as we like, there remains to produce a quantitative measure to assess how likely each of these profiles is, what the appropriate 'average' profile should be, and what the 'variance' of these multiple solutions is. Of course, in order to do this, one needs to spell out the stochastic constraints that can allow us to make sense of the words 'average' and 'variance' in a mathematically rigorous way. Such a quantitative approach would be particularly well-suited for such systems as the proposed Precipitation Radar of the Tropical Rainfall Measuring Mission (TRMM). Indeed, one would then be able to use the radar reflectivities measured by the TRMM radar from one particular look in order to estimate the most likely rain-rate profile that would have produced the measurements, as well as the uncertainty in the estimated rain-rates as a function of range. Such an optimal approach is described in this paper.

deep space flight computer real-time advanced spac↗
DOE OSTI2013

A TWO-YEAR TIME DELAY FOR THE LENSED QUASAR SDSS J1029+2623

We present 279 epochs of optical monitoring data spanning 5.4 years from 2007 January to 2012 June for the largest image separation (22.''6) gravitationally lensed quasar, SDSS J1029+2623. We find that image A leads the images B and C by {Delta} t {sub AB} = (744 {+-} 10) days (90% confidence); the uncertainty includes both statistical uncertainties and systematic differences due to the choice of models. With only a {approx}1% fractional error, the interpretation of the delay is limited primarily by cosmic variance due to fluctuations in the mean line-of-sight density. We cannot separate the fainter image C from image B, but since image C trails image B by only 2-3 days in all models, the estimate of the time delay between images A and B is little affected by combining the fluxes of images B and C. There is weak evidence for a low level of microlensing, perhaps created by the small galaxy responsible for the flux ratio anomaly in this system. Interpreting the delay depends on better constraining the shape of the gravitational potential using the lensed host galaxy, other lensed arcs, and the structure of the X-ray emission.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2013

EFFECT OF MASKED REGIONS ON WEAK-LENSING STATISTICS

Sky masking is unavoidable in wide-field weak-lensing observations. We study how masks affect the measurement of statistics of matter distribution probed by weak gravitational lensing. We first use 1000 cosmological ray-tracing simulations to examine in detail the impact of masked regions on the weak-lensing Minkowski Functionals (MFs). We consider actual sky masks used for a Subaru Suprime-Cam imaging survey. The masks increase the variance of the convergence field and the expected values of the MFs are biased. The bias then compromises the non-Gaussian signals induced by the gravitational growth of structure. We then explore how masks affect cosmological parameter estimation. We calculate the cumulative signal-to-noise ratio (S/N) for masked maps to study the information content of lensing MFs. We show that the degradation of S/N for masked maps is mainly determined by the effective survey area. We also perform simple {chi}{sup 2} analysis to show the impact of lensing MF bias due to masked regions. Finally, we compare ray-tracing simulations with data from a Subaru 2 deg{sup 2} survey in order to address if the observed lensing MFs are consistent with those of the standard cosmology. The resulting {chi}{sup 2}/n{sub dof} = 29.6/30 for three combined MFs, obtained with the mask effects taken into account, suggests that the observational data are indeed consistent with the standard {Lambda}CDM model. We conclude that the lensing MFs are a powerful probe of cosmology only if mask effects are correctly taken into account.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

SHORT ACCELERATION TIMES FROM SUPERDIFFUSIVE SHOCK ACCELERATION IN THE HELIOSPHERE

The analysis of time profiles of particles accelerated at interplanetary shocks allows particle transport properties to be inferred. The frequently observed power-law decay upstream, indeed, implies a superdiffusive particle transport when the level of magnetic field variance does not change as the time interval from the shock front increases. In this context, a superdiffusive shock acceleration (SSA) theory has been developed, allowing us to make predictions of the acceleration times. In this work we estimate for a number of interplanetary shocks, including the solar wind termination shock, the acceleration times for energetic protons in the framework of SSA and we compare the results with the acceleration times predicted by standard diffusive shock acceleration. The acceleration times due to SSA are found to be much shorter than in the classical model, and also shorter than the interplanetary shock lifetimes. This decrease of the acceleration times is due to the scale-free nature of the particle displacements in the framework of superdiffusion. Indeed, very long displacements are possible, increasing the probability for particles far from the front of the shock to return, and short displacements have a high probability of occurrence, increasing the chances for particles close to the front to cross the shock many times.

79 ASTRONOMY AND ASTROPHYSICS↗