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At least 1,711 records · Page 95
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Predicting spring phenology in deciduous broadleaf forests: NEON phenology forecasting community challenge

Accurate models are important to predict how global climate change will continue to alter plant phenology and near-term ecological forecasts can be used to iteratively improve models and evaluate predictions that are made a priori. The Ecological Forecasting Initiative's National Ecological Observatory Network (NEON) Forecasting Challenge, is an open challenge to the community to forecast daily greenness values, measured through digital images collected by the PhenoCam Network at NEON sites before the data are collected. For the first round of the challenge, which is presented here, we forecasted canopy greenness throughout the spring at eight deciduous broadleaf sites to investigate when, where, and for what model type phenology forecast skill is highest. A total of 192,536 predictions were submitted, representing eighteen models, including a persistence and a day of year mean null models. We found that overall forecast skill was highest when forecasting earlier in the greenup curve compared to the end, for shorter lead times, for sites that greened up earlier, and when submitting forecasts during times other than near budburst. The models based on day of year historical mean had the highest predictive skill across the challenge period. In this first round of the challenge, by synthesizing across forecasts, we started to elucidate what factors affect the predictive skill of near-term phenology forecasts.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Ten questions concerning Large Language Models (LLMs) for building applications

Large Language Models (LLMs) are emerging as powerful AI tools capable of transforming how building information is collected, processed, analyzed, and applied across diverse research areas. Their capabilities can help building operators, facility managers and other stakeholders such as designers, architects and engineers by providing actionable insights for decision-making across planning, construction, operations, and maintenance of buildings and facilities. This paper explores ten key questions concerning the role of LLMs in shaping sustainable, intelligent, and human-centric buildings. From fundamental definitions to advanced applications, we examine how LLMs facilitate decision-making across the life cycle of buildings and energy systems. LLMs can enhance life cycle assessments (LCA), building energy simulations, and real-time data integration, empowering more efficient and adaptive human-AI environments. They can also contribute to streamlining regulatory compliance, improving post-occupancy evaluations, and fostering more inclusive and participatory design processes. Additionally, this paper addresses the ethical challenges posed by LLMs, such as bias, data privacy, and environmental impacts, and explores their potentials in advancing intelligent digital twins (DT) for ongoing building operations and maintenance. Built upon our applied research using LLMs and the review of tools, datasets, and research gaps, we provide a forward-looking perspective on how LLMs can drive innovation, collaboration, and productivity in the built environment while supporting ethical and effective implementation.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2015

Pulse shape discrimination performance of stilbene coupled to low-noise silicon photomultipliers

Pulse shape discrimination (PSD) techniques can be used to discern between neutron and gamma-ray interactions in certain organic scintillators. Traditionally, photomultiplier tubes (PMTs) have been used in organic-scintillator assemblies. However, silicon photomultipliers (SiPMs) have great potential to be used in many applications in which PMTs have been predominantly used, including those utilizing PSD techniques. To evaluate the current state of the art of the SiPM technology, SensL's 6-mm B-Series and C-Series SiPMs were compared to a fast Hamamatsu PMT in conjunction with a 6×6×6-mm3 stilbene organic scintillator to assess the PSD performance of the detector assemblies. Measurements with a Cf-252 source were performed and a figure of merit (FOM) for discriminating between neutron and gamma-ray pulses between 100 keVee and 200 keVee was calculated for each assembly. A digital charge-integration PSD technique was used to process all measured data. The FOM for the B-Series SiPM, PMT, and C-Series SiPM was 1.37, 1.93, and 2.13, respectively. The C-Series SiPM was shown to perform as well as the PMT in the experiments.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2018

The NOvA power distribution system

We describe the power distribution systems and grounding schemes built for the near and far detectors of the NOvA long-baseline neutrino experiment. They are used to power the avalanche photodiodes and their thermoelectric coolers, the front-end boards that read out, digitize and time stamp the signals from the avalanche photodiodes, and the data concentrator modules used to receive and format the data from the front-end boards before sending them to a farm of computers used to build the events. Furthermore, the system powers 344,064 readout channels in the far detector and 20,192 channels in the near detector.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Direct Observations of Solute Dispersion in Rocks With Distinct Degree of Sub‐Micron Porosity

Abstract The transport of chemical species in rocks is affected by their structural heterogeneity to yield a wide spectrum of local solute concentrations. To quantify such imperfect mixing, advanced methodologies are needed that augment the traditional breakthrough curve analysis by probing solute concentration within the fluids locally. Here, we demonstrate the application of asynchronous, multimodality imaging by X‐ray computed tomography (XCT) and positron emission tomography (PET) to the study of passive tracer experiments in laboratory rock cores. The four‐dimensional concentration maps measured by PET reveal specific signatures of the transport process, which we have quantified using fundamental measures of mixing and spreading. We observe that the extent of solute spreading correlate strongly with the strength of subcore‐scale porosity heterogeneity measured by XCT, while dilution is enhanced in rocks containing substantial sub‐micron porosity. We observe that the analysis of different metrics is necessary, as they can differ in their sensitivity to the strength and forms of heterogeneity. The multimodality imaging approach is uniquely suited to probe the fundamental difference between spreading and mixing in heterogeneous media. We propose that when multi‐dimensional data is available, mixing and spreading can be independently quantified using the same metric. We also demonstrate that one‐dimensional transport models have limited predictive ability toward the internal evolution of the solute concentration, when the model is solely calibrated against the effluent breakthrough curves. The data set generated in this study can be used to build realistic digital rock models and to benchmark transport simulations that account deterministically for rock property heterogeneity.

Kurotori, Takeshi [Department of Chemical Engineer↗
DOE OSTI2023

An efficient instance segmentation approach for studying fission gas bubbles in irradiated metallic nuclear fuel

Abstract Gaseous fission products from nuclear fission reactions tend to form fission gas bubbles of various shapes and sizes inside nuclear fuel. The behavior of fission gas bubbles dictates nuclear fuel performances, such as fission gas release, grain growth, swelling, and fuel cladding mechanical interaction. Although mechanical understanding of the overall evolution behavior of fission gas bubbles is well known, lacking the quantitative data and high-level correlation between burnup/temperature and microstructure evolution blocks the development of predictive models and reduces the possibility of accelerating the qualification for new fuel forms. Historical characterization of fission gas bubbles in irradiated nuclear fuel relied on a simple threshold method working on low-resolution optical microscopy images. Advanced characterization of fission gas bubbles using scanning electron microscopic images reveals unprecedented details and extensive morphological data, which strains the effectiveness of conventional methods. This paper proposes a hybrid framework, based on digital image processing and deep learning models, to efficiently detect and classify fission gas bubbles from scanning electron microscopic images. The developed bubble annotation tool used a multitask deep learning network that integrates U-Net and ResNet to accomplish instance-level bubble segmentation. With limited annotated data, the model achieves a recall ratio of more than 90%, a leap forward compared to the threshold method. The model has the capability to identify fission gas bubbles with and without lanthanides to better understand the movement of lanthanide fission products and fuel cladding chemical interaction. Lastly, the deep learning model is versatile and applicable to the micro-structure segmentation of similar materials.

36 MATERIALS SCIENCE↗
DOE OSTI2012

COMPARISON OF TWO EPOCHS OF THE ZEEMAN EFFECT IN THE 44 GHz CLASS I METHANOL (CH{sub 3}OH) MASER LINE IN OMC-2

We present a second epoch of observations of the 44 GHz Class I methanol maser line toward the star-forming region Orion Molecular Cloud 2. The observations were carried out with the Very Large Array, and constitute one of the first successful Zeeman effect detections with the new Wide-band Digital Architecture correlator. Comparing to the result of our earlier epoch of data for this region, we find that the intensity of the maser increased by 50%, but the magnetic field value has stayed the same, within the errors. This suggests that the methanol maser may be tracing the large-scale magnetic field that is not affected by the bulk gas motions or turbulence on smaller scales that is causing the change in maser intensity.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

PRIMUS: Effects of galaxy environment on the quiescent fraction evolution at z < 0.8

We investigate the effects of galaxy environment on the evolution of the quiescent fraction (f{sub Q}) from z=0.8 to 0.0 using spectroscopic redshifts and multi-wavelength imaging data from the PRIsm MUlti-object Survey (PRIMUS) and the Sloan Digital Sky Survey (SDSS). Our stellar mass limited galaxy sample consists of ∼14,000 PRIMUS galaxies within z = 0.2–0.8 and ∼64,000 SDSS galaxies within z = 0.05–0.12. We classify the galaxies as quiescent or star-forming (SF) based on an evolving specific star formation cut, and as low or high density environments based on fixed cylindrical aperture environment measurements on a volume-limited environment defining population. For quiescent and SF galaxies in low or high density environments, we examine the evolution of their stellar mass function (SMF). Then using the SMFs we compute f{sub Q}(M{sub ∗}) and quantify its evolution within our redshift range. We find that the quiescent fraction is higher at higher masses and in denser environments. The quiescent fraction rises with cosmic time for all masses and environments. At a fiducial mass of 10{sup 10.5} M{sub ⊙}, from z∼0.7 to 0.1, the quiescent fraction rises by 15% at the lowest environments and by 25% at the highest environments we measure. These results suggest that for a minority of galaxies their cessation of star formation is due to external influences on them. In other words, in the recent universe a substantial fraction of the galaxies that cease forming stars do so due to internal processes.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

The clustering of galaxies in the completed SDSS-III Baryon Oscillation Spectroscopic Survey: On the measurement of growth rate using galaxy correlation functions

We present a measurement of the linear growth rate of structure, ƒ, from the Sloan Digital Sky Survey III (SDSS-III) Baryon Oscillation Spectroscopic Survey (BOSS) Data Release 12 (DR12) using convolution Lagrangian perturbation theory (CLPT) with Gaussian streaming redshift space distortions (GSRSD) to model the two-point statistics of BOSS galaxies in DR12. The BOSS-DR12 data set includes 1198 006 massive galaxies spread over the redshift range 0.2 < z < 0.75. These galaxy samples are categorized in three redshift bins. Using CLPT-GSRSD in our analysis of the combined sample of the three redshift bins, we report measurements of fσ8 for the three redshift bins. We find ƒσ 8 = 0.430 ± 0.054 at z eff = 0.38, ƒσ 8 = 0.452 ± 0.057 at z eff = 0.51 and ƒσ 8 = 0.457 ± 0.052 at z eff = 0.61. Our results are consistent with the predictions of Planck Λ cold dark matter-general relativity. Our constraints on the growth rates of structure in the Universe at different redshifts serve as a useful probe, which can help distinguish between a model of the Universe based on dark energy and models based on modified theories of gravity. This paper is part of a set that analyses the final galaxy clustering data set from BOSS. Lastly, the measurements and likelihoods presented here are combined with others in Alam et al., to produce the final cosmological constraints from BOSS.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

A 32-Channel Cryo-CMOS ASIC for SNSPD Biasing and Readout with Picosecond

Superconducting nanowire single-photon detectors (SNSPD) are a promising technology for particle detection. Although SNSPDs have demonstrated picosecond timing accuracy, scaling up large arrays has proved challenging. In this work, we introduce a 32-channel cryo-CMOS application-specific integrated circuit (ASIC) that can be tightly integrated with SNSPD arrays. The ASIC is designed to operate at a temperature of 4K and can perform up to 32 simultaneous timing measurements with a root-mean-square (RMS) accuracy of 8.0ps. The ASIC includes on-chip circuitry for externally biasing superconducting devices, low-noise amplifiers for reading superconducting devices, high-resolution time-to-digital converters (TDC) for time-tagging events, and serializers for transmitting data to room-temperature electronics. The ASIC is manufactured in a 22nm FDSOI process and occupies an area of 4.0mm x 1.0mm. The performance of the ASIC was verified using custom cryogenic device models internally developed for the 22nm SOI process. Measurement results will be presented at the conference.

Fredenburg, Jeff↗
DOE OSTI2015

Modeling and Analysis of Hybrid Pixel Detector Deficiencies for Scientific Applications

Semiconductor hybrid pixel detectors often consist of a pixellated sensor layer bump bonded to a matching pixelated readout integrated circuit (ROIC). The sensor can range from high resistivity Si to III-V materials, whereas a Si CMOS process is typically used to manufacture the ROIC. Independent, device physics and electronic design automation (EDA) tools are used to determine sensor characteristics and verify functional performance of ROICs respectively with significantly different solvers. Some physics solvers provide the capability of transferring data to the EDA tool. However, single pixel transient simulations are either not feasible due to convergence difficulties or are prohibitively long. A simplified sensor model, which includes a current pulse in parallel with detector equivalent capacitor, is often used; even then, spice type top-level (entire array) simulations range from days to weeks. In order to analyze detector deficiencies for a particular scientific application, accurately defined transient behavioral models of all the functional blocks are required. Furthermore, various simulations, such as transient, noise, Monte Carlo, inter-pixel effects, etc. of the entire array need to be performed within a reasonable time frame without trading off accuracy. The sensor and the analog front-end can be modeling using a real number modeling language, as complex mathematical functions or detailed data can be saved to text files, for further top-level digital simulations. Parasitically aware digital timing is extracted in a standard delay format (sdf) from the pixel digital back-end layout as well as the periphery of the ROIC. For any given input, detector level worst-case and best-case simulations are performed using a Verilog simulation environment to determine the output. Each top-level transient simulation takes no more than 10-15 minutes. The impact of changing key parameters such as sensor Poissonian shot noise, analog front-end bandwidth, jitter due to clock distribution etc. can be accurately analyzed to determine ROIC architectural viability and bottlenecks. Hence the impact of the detector parameters on the scientific application can be studied.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2014

Multichannel response analysis on 2D projection views for detection of clustered microcalcifications in digital breast tomosynthesis

Purpose: To investigate the feasibility of a new two-dimensional (2D) multichannel response (MCR) analysis approach for the detection of clustered microcalcifications (MCs) in digital breast tomosynthesis (DBT). Methods: With IRB approval and informed consent, a data set of two-view DBTs from 42 breasts containing biopsy-proven MC clusters was collected in this study. The authors developed a 2D approach for MC detection using projection view (PV) images rather than the reconstructed three-dimensional (3D) DBT volume. Signal-to-noise ratio (SNR) enhancement processing was first applied to each PV to enhance the potential MCs. The locations of MC candidates were then identified with iterative thresholding. The individual MCs were decomposed with Hermite–Gaussian (HG) and Laguerre–Gaussian (LG) basis functions and the channelized Hotelling model was trained to produce the MCRs for each MC on the 2D images. The MCRs from the PVs were fused in 3D by a coincidence counting method that backprojects the MC candidates on the PVs and traces the coincidence of their ray paths in 3D. The 3D MCR was used to differentiate the true MCs from false positives (FPs). Finally a dynamic clustering method was used to identify the potential MC clusters in the DBT volume based on the fact that true MCs of clinical significance appear in clusters. Using two-fold cross validation, the performance of the 3D MCR for classification of true and false MCs was estimated by the area under the receiver operating characteristic (ROC) curve and the overall performance of the MCR approach for detection of clustered MCs was assessed by free response receiver operating characteristic (FROC) analysis. Results: When the HG basis function was used for MCR analysis, the detection of MC cluster achieved case-based test sensitivities of 80% and 90% at the average FP rates of 0.65 and 1.55 FPs per DBT volume, respectively. With LG basis function, the average FP rates were 0.62 and 1.57 per DBT volume at the same sensitivity levels. The difference in the two sets of basis functions for detection of MCs did not show statistical significance. Conclusions: The authors' experimental results indicate that the MCR approach is promising for the detection of MCs on PV images. The HG or LG basis functions are both effective in characterizing the signal response of MCs using the channelized Hotelling model. The coincidence counting method for fusion of the 2D MCR in 3D is an important step for FP reduction. Further study is underway to improve the MCR approach for microcalcification detection in DBT.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2014

SU-E-J-231: Comparison of 3D Angiogram and MRI in Delineating the AVM Target for Frameless Stereotactic Radiosurgery

Purpose: Stereotactic radiation therapy (SRT) provides an excellent alternative to embolization and surgical excision for the management of appropriately selected cerebral arteriovenous malformations (AVMs). The currently accepted standard for delineating AVMs is planar digital subtraction angiography (DSA). DSA can be used to acquire a 3D data set that preserves osseous structures (3D-DA) at the time of the angiography for SRT planning. Magnetic resonance imaging (MRI) provides an alternative noninvasive method of visualizing the AVM nidus with comparable spatial resolution. We utilized 3D-DA and T1 post-contrast MRI data to evaluate the differences in SRT target volumes. Methods: Four patients underwent 3D-DA and high-resolution MRI. 3D T1 post-contrast images were obtained in all three reconstruction planes. A planning CT was fused with MRI and 3D-DA data sets. The AVMs were contoured utilizing one of the image sets at a time. Target volume, centroid, and maximum and minimum dimensions were analyzed for each patient. Results: Targets delineated using post-contrast MRI demonstrated a larger mean volume. AVMs >2 cc were found to have a larger difference between MRI and 3D-DA volumes. Larger AVMs also demonstrated a smaller relative uncertainty in contour centroid position (1 mm). AVM targets <2 cc had smaller absolute differences in volume, but larger differences in contour centroid position (2.5 mm). MRI targets demonstrated a more irregular shape compared to 3D-DA targets. Conclusions: Our preliminary data supports the use of MRI alone to delineate AVM targets >2 cc. The greater centroid stability for AVMs >2 cc ensures accurate target localization during image fusion. The larger MRI target volumes did not result in prohibitively greater volumes of normal brain tissue receiving the prescription dose. The larger centroid instability for AVMs <2 cc precludes the use of MRI alone for target delineation. We recommend incorporating a 3D-DA for these patients.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2026

Timeseries Photos of a Variably Inundated Stream: Umtanum Creek, Washington, United States

This dataset is associated with a broader study using game camera timeseries photos collected to evaluate stream variable inundation via changes in width (i.e. wet fraction). Four game cameras were deployed along Umtanum Creek (Washington, United States) to track changes in stream inundation over time. Drone imagery was collected at the same location on October 18, 2024 which was used to construct a digital elevation model (DEM) of the streambed topography. The associated paper and data can be found at https://doi.org/10.1016/j.envsoft.2025.106715 (Bao et al., 2025a)) and https://doi.org/10.15485/2589885 (Bao et al., 2025b), respectively. For details on how to navigate data packages generated by this project, see https://data.ess-dive.lbl.gov/portals/PNNLRiverCorridorSFA/About. In addition to this readme, this data package also includes a file-level metadata (FLMD) files that describes each file and a data dictionaries (DD) that describe all column/row headers and variable definitions. This dataset is comprised of (1) file-level metadata; (2) data dictionary; (3) readme; (4) field metadata; (5) field protocol; and (5) folders containing game camera photos. Game camera photos are organized into folders for each camera (CDL, CUL, CDR, CUR; see readme for information on camera naming) by the month photos were collected. All files are .csv, .jpg, or .pdf.

AI image segmentation↗
DOE OSTI2012

NMIS with Imaging and Gamma Ray Spectrometry for Pu, HEU, HE and Other Materials

The Nuclear Material Identification System (NMIS) has been under development at ORNL and the National Nuclear Security Administration (NNSA) Y-12 National Security Complex since 1984. In the mid-1990s, what is now the US Department of Energy (DOE) Office of Nuclear Verification (ONV) realized that it was a useful technology for future arms control treaty applications and supported further development of the system. In 2004, fast-neutron imaging was incorporated into the system. In 2007, the ONV decided to develop a fieldable version of the system, designated as FNMIS, for potential use in future treaties. The FNMIS is being developed to be compatible with the eventual incorporation of gamma-ray spectrometry and an information barrier. This report addresses how and what attributes could be determined by the FNMIS system with gamma-ray spectrometry. The NMIS is a time-dependent coincidence system that incorporates tomographic imaging (including mapping of the fission sites) and gamma-ray spectrometry. It utilizes a small, lightweight (30 lb), portable deuterium-tritium (DT) neutron (14.1 MeV) generator (4 x 10 7 neutrons/second) for active interrogation and can also perform passive interrogation. A high-purity germanium (HPGe) gamma-ray detector with multichannel analysis can be utilized in conjunction with the source for active interrogation or passively. The system uses proton recoil scintillators: 32 small 2.5 x 2.5 x 10.2-cm-thick plastic scintillators for imaging and at least two 2 x 2 arrays of 27 x 27 x 10-cm-thick plastic scintillators that detect induced fission radiation. The DT generator contains an alpha detector that time and directionally tags a fan beam of some of the neutrons emitted and subdivides it into pixels. A fast (1 GHz) time correlation processor measures the time-dependent coincidence among all detectors in the system. A computer-controlled scanner moves the small detectors and the source appropriately for scanning a target object for imaging. The system is based on detection of transmitted 14.1 MeV neutrons, fission neutrons, and gamma rays from spontaneous, inherent source fission of the target, fission neutrons and gamma rays induced by the external DT source, gamma rays from natural emissions of uranium and plutonium, and induced gamma-ray emission by the interaction of the 14.1 MeV neutrons from the DT source. The NMIS can and has been used with a time-tagged californium spontaneous fission source. It has also been used with pulsed interrogation sources such as LINACs, DT, and deuterium-deuterium (DD) sources. This system is uniquely suited for detection of shielded highly enriched uranium (HEU), plutonium, and other special nuclear materials and detection of high explosives (HE) and chemical agents. The NMIS will be adapted to utilize a trusted processor that incorporates information barrier and authentication techniques using open software and then be useful in some international applications for materials whose characteristics may be classified. The proposed information barrier version of the NMIS system would consist of detectors and cables, the red (classified side) computer system, which processes the data, and the black (unclassified side) computer, which handles the computer interface. The system could use the 'IB wrapper' concept proposed by Los Alamos National Laboratory and the software integrity (digital signatures) system proposed by Sandia. Since it is based entirely on commercially available components, the entire system, including NMIS data acquisition boards, can be built with commercial off-the-shelf components. This system is being developed into a fieldable system (FNMIS) for potential arms control treaties by the ONV. The system will be modularly constructed with the RF shielded modules connected to the processor by appropriate control and signal cable in metal conduit. The FNMIS is presently being designed for eventual incorporation of gamma-ray spectrometry and an information barrier to protect classified information. The system hardware and software can be configured to obtain the following: plutonium presence, plutonium mass, Pu-240/239 ratio, plutonium geometry, plutonium metal vs non-metallic (absence of metal), time (age) since processing for plutonium (or last purification), uranium presence, uranium mass, uranium enrichment, uranium geometry, uranium metal vs non-metallic compound (absence of metal), beryllium presence and mass, tritium and deuterium gas bottle presence, HE, and chemical weapons. A matrix of the quantities determined, the method of determination, whether active (external neutron source) or passive, and the measurement equipment involved is given in the Tables 1-4. Some of these attributes can be obtained by multiple data analysis methods. The gamma-ray spectrometry methods for HEU, plutonium, and HE have been developed by other laboratories, are well known, and will be incorporated.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2012

Detailed Hydrographic Feature Extraction from High-Resolution LiDAR Data

Detailed hydrographic feature extraction from high-resolution light detection and ranging (LiDAR) data is investigated. Methods for quantitatively evaluating and comparing such extractions are presented, including the use of sinuosity and longitudinal root-mean-square-error (LRMSE). These metrics are then used to quantitatively compare stream networks in two studies. The first study examines the effect of raster cell size on watershed boundaries and stream networks delineated from LiDAR-derived digital elevation models (DEMs). The study confirmed that, with the greatly increased resolution of LiDAR data, smaller cell sizes generally yielded better stream network delineations, based on sinuosity and LRMSE. The second study demonstrates a new method of delineating a stream directly from LiDAR point clouds, without the intermediate step of deriving a DEM. Direct use of LiDAR point clouds could improve efficiency and accuracy of hydrographic feature extractions. The direct delineation method developed herein and termed “mDn”, is an extension of the D8 method that has been used for several decades with gridded raster data. The method divides the region around a starting point into sectors, using the LiDAR data points within each sector to determine an average slope, and selecting the sector with the greatest downward slope to determine the direction of flow. An mDn delineation was compared with a traditional grid-based delineation, using TauDEM, and other readily available, common stream data sets. Although, the TauDEM delineation yielded a sinuosity that more closely matches the reference, the mDn delineation yielded a sinuosity that was higher than either the TauDEM method or the existing published stream delineations. Furthermore, stream delineation using the mDn method yielded the smallest LRMSE.

58 GEOSCIENCES↗
DOE OSTI2023

High Energy Quasi - Differential Neutron Emission Measurements of 181 Ta and 19 F [Slides]

This presentation begins with the motivation for performing 181 Ta and 19 F high energy quasi-differential and neutron emission measurements. It then provides a discussion of significant pulse digitization upgrade. The Quasi-Differential methodology and importance for validating nuclear data are provided. Preliminary results from 181 Ta and 19 F are displayed. The presentation concludes with a discussion and future studies.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗