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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 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Modeling forest site productivity using mapped geospatial attributes within a South Carolina Landscape, USA

Spatially explicit mapping of forest productivity is important to assess many forest management alternatives. We assessed the relationship between mapped variables and site index of forests ranging from southern pine plantations to natural hardwoods on a 74,000-ha landscape in South Carolina, USA. Mapped features used in the analysis were soil association, land use condition in 1951, depth to groundwater, slope and aspect. Basal area, species composition, age and height were the tree variables measured. Linear modelling identified that plot basal area, depth to groundwater, soils association and the interactions between depth to groundwater and forest group, and between land use in 1951 and forest group were related to site index (SI) (R 2 =0.37), but this model had regression attenuation. We then used structural equation modeling to incorporate error-in-measurement corrections for basal area and groundwater to remove bias in the model. We validated this model using 89 independent observations and found the 95% confidence intervals for the slope and intercept of an observed vs. predicted site index error-corrected regression included zero and one, respectively, indicating a good fit. With error in measurement incorporated, only basal area, soil association, and the interaction between forest groups and land use were important predictors (R2 =0.57). Thus, we were able to develop an unbiased model of SI that could be applied to create a spatially explicit map based primarily on soils as modified by past (land use and forest type) and recent forest management (basal area).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Attribution of heterogeneous stress distributions in low-grain polycrystals under conditions leading to damage

In high-purity polycrystalline metallic materials, voids tend to favor grain boundaries as nucleation sites due to the elevated stress states produced by granular interactions and the weakened grain boundary from the relative atomic disorder. To quantify the key factors of this elevated stress state, simple compression of a small multi-grain cylinder of body-centered cubic tantalum was simulated using a single crystal plasticity model that incorporates non-Schmid effects. Four increasingly complex synthetic microstructures were created to tractably incorporate grain boundary interactions, and a statistically significant number of combinations were performed by varying the initial crystallographic orientations of the microstructure. Most of these simulations produce the maximum von Mises stress on a grain boundary and less frequently at the multi-grain junctions. To build a statistical model for the maximum von Mises stress at the grain boundary, physically based features that could contribute to the elevated stress state were selected. Then, a learning algorithm based on information theory was used to identify which of these features contributed the most information to the data set. The identified features include a grain’s propensity to accommodate both elastic and plastic deformations and their directional components. The misalignment of the direction of each grain’s mechanical response was found to be strongly correlated to the magnitude of the stress near the grain boundary. For all of the synthetic microstructures, the statistical models produce a residual distribution that is nearly Gaussian with a variance of, at most, 10% of the prior distribution. The successful performance of the statistical model implies the correct identification of the physical features that cause severe stress localization in polycrystalline materials. The statistical models constructed here can be used to formulate a physically motivated void nucleation model which is sensitive to a microstructure’s propensity to produce elevated stress states. As a result, these statistical models also enable the design of material microstructures, in which the crystallographic orientation is chosen to resist void nucleation.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Detection and attribution of long-term and fine-scale changes in spring phenology over urban areas: A case study in New York State

Spring phenology plays an essential role in climate change, terrestrial ecosystem, and public health. Field-based monitoring and understanding of changes in spring phenology for long periods and in large regions are challenging due to the limited in-site observations. Space-based remotely sensed observations offer great potentials for monitoring decadal spring phenology changes from regional to global scales. However, the coarse-scale remotely sensed observations are insufficient to capture fine-scale spring phenology dynamics, especially in urban areas, and this makes it challenging for understanding the combined effects of climate change and urbanization on spring phenology. We derived the start of phenology season (SOS) in New York State using 30 m Landsat observations from 1990 to 2015 to understand the impact of the environment and urbanization on SOS. The results show that SOS for different years reveals heterogeneous spatial distribution. Most regions of New York State have been experiencing significant spring phenology changes in form of earlier onset of vegetation greening, ranging from 0.2 to 0.6 day/year during 1990 to 2015, and this trend varies slightly with latitudes and urbanization levels. Further, spatial correlation analysis shows that the increase in temperature and urbanization could both promote the advancement of SOS. However, the effect of urbanization (partial correlation coefficient (R) ranges from −0.289 to −0.542) on SOS is greater than the effect of temperature (R ranges from 0.006 to −0.192). The study generates a high spatio-temporal resolution spring phenology dataset for ecological, environmental and public health studies, especially in urban areas, and reveals the importance of better accounting for the urbanization effects when quantifying the SOS dynamics in phenology models.

Landsat↗
DOE OSTI2018

Attribution of gamma-ray background collected by a mobile detector system to its surroundings using panoramic video

Mobile radiation detector systems are important tools for detecting radiological and nuclear sources outside of regulatory control, but due to their mobility, they are subject to complex and varying backgrounds in most realistic operational scenarios. Recent work has found correlations between non-radiological contextual information and gamma-ray spectral features that can be used to decrease false alarm rates, however a more complete understanding of background source terms has been elusive. A measurement campaign developed a full radiological characterization of a controlled facility that roughly corresponded to two city blocks. As part of the campaign, the Radiological Multi-sensor Analysis Platform (RadMAP) collected extensive multi-sensor data. In this work, RadMAP’s panoramic video data were used to visually identify several different materials and quantify the detector response to each material. A linear model was fit between the material responses and radiological features, and the results demonstrate reasonable agreement with ground truth flux measurements for each material. This paper will describe the data collection, processing, and analysis of the gamma-ray and video data from RadMAP. The paper will conclude with perspectives on the applicability of such a method to less controlled environments both with respect to achieving better understanding the sources of variability of background radiation in urban environments and whether such methods could be leveraged in operational scenarios.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

A simulation pipeline for fast neutron imaging and spectroscopy using quantified detector attributes

Radiation imaging capabilities, essential in the nuclear nonproliferation regime, facilitate source localization and, in certain cases, spectroscopy. Scatter-based neutron cameras, which can measure the neutron signatures from special nuclear material, hold particular interest. Systems incorporating organic scintillators can extract neutron energy spectra, potentially distinguishing fission neutron sources from others, such as alpha-neutron sources. The development and testing of a scatter-based neutron imager, however, can be challenging without having an accurate simulation model or first constructing a prototype. This work describes a simulation pipeline that takes output from MCNPX-PoliMi simulations and creates the expected back-projection neutron images and neutron energy spectra. This pipeline was developed to improve the modeling of fast neutron imagers and bridge the current gap in literature, which predominantly focuses on gamma-ray Compton imager models. This work also reports on the significance of various real-world system considerations and their effects on the simulated detector responses. The pipeline was verified and validated with experimental data collected using a 252 Cf spontaneous fission source using a fast neutron scattering imager developed at the University of Michigan.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2017

Attribution of PM 2.5 exposure in Beijing–Tianjin–Hebei region to emissions: implication to control strategies

The Beijing–Tianjin–Hebei (BTH) region is one of the most heavily polluted regions in China, with both high PM 2.5 concentrations and a high population density. A quantitative source-receptor relationship can provide valuable insights that can inform effective emission control strategies. Both source apportionment (SA) and source sensitivity (SS) can provide such information from different perspectives. In this study, both methods are applied in northern China to identify the most significant emission categories and source regions for PM 2.5 exposure in BTH in 2013. Despite their differences, both models show similar distribution patterns for population and simulated PM 2.5 concentrations, resulting in overall high PM 2.5 exposure values (approximately 110 μg/m 3 ) and particularly high exposure values during the winter (approximately 200 μg/m 3 ). Both methods show that local emissions play a dominant role (70%), with some contribution from surrounding provinces (e.g., Shandong) via regional transport. The two methods also agree on the priority of local emission controls: both identify industrial, residential, and agricultural emissions as the top three categories that should be controlled locally. In addition, the effect of controlling agricultural ammonia emissions is approximately doubled when the co-benefits of reducing nitrate are considered. In conclusion, the synthesis of SA and SS for addressing specific categories of emissions provides a quantitative basis for the development of emission control strategies and policies for controlling PM 2.5 in China.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2017

Elemental source attribution signatures for calcium ammonium nitrate (CAN) fertilizers used in homemade explosives

Calcium ammonium nitrate (CAN) is a widely available fertilizer composed of ammonium nitrate mixed with some form of calcium carbonate such as limestone or dolomite. CAN is also frequently used to make homemade explosives. The potential of using elemental profiling and chemometrics to match both pristine and reprocessed CAN fertilizers to their factories for use in future forensic investigations was examined. Inductively coupled plasma-mass spectrometry (ICP-MS) analysis was performed on 64 elements in 125 samples from 11 CAN stocks from 6 different CAN factories. Fisher ratio, degree-of-class-separation, and partial least squares discriminant analysis (PLSDA) were used to develop a model using the concentrations of Na, V, Mn, Cu, Ga, Sr, Ba and U to classify a validation set of CAN samples into 5 factory groups; one group was two factories from the same fertilizer company. In terms of the pristine CAN samples, i.e., unadulterated prills, 64% of the test samples were matched to their correct factory group with zero false positives. The same PLSDA model was used to correctly match 100% of the CAN samples that were reprocessed by crushing and mixing the CAN with powdered sugar. In the case of crushed CAN samples mixed with aluminum powder, correct matches were made for zero to 100% of the samples depending on the factory the CAN originated. Remarkably, for one factory, 100% of the ammonium nitrate samples that were extracted from CAN using tap or bottled water were matched to the correct CAN factory group. Lastly, the water-insoluble (calcium carbonate) portions of CAN provided a greater degree of discrimination between factories than the water-soluble portions of CAN. In summary, this work illustrates that sourcing unadulterated CAN fertilizer can potentially be done with high frequency and high confidence using elemental profiling and chemometrics while the sourcing of reprocessed CAN is dependent on how much an adulterant alters the recovered elemental profile of CAN.

chemical forensics↗