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At least 1,513 records · Page 84
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

SU-F-T-513: Dosimetric Validation of Spatially Fractionated Radiotherapy Using Gel Dosimetry

Purpose: Spatially fractionated radiation therapy, also known as GRID therapy, is used to treat large solid tumors by irradiating the target to a single dose of 10–20Gy through spatially distributed beamlets. We have investigated the use of a 3D gel for dosimetric characterization of GRID therapy. Methods: GRID therapy is an external beam analog of volumetric brachytherapy, whereby we produce a distribution of hot and cold dose columns inside the tumor volume. Such distribution can be produced with a block or by using a checker-like pattern with MLC. We have studied both types of GRID delivery. A cube shaped acrylic phantom was filled with polymer gel and served as a 3D dosimeter. The phantom was scanned and the CT images were used to produce two plans in Pinnacle, one with the grid block and one with the MLC defined grid. A 6MV beam was used for the plan with a prescription of 1500cGy at dmax. The irradiated phantom was scanned in a 3T MRI scanner. Results: 3D dose maps were derived from the MR scans of the gel dosimeter and were found to be in good agreement with the predicted dose distribution from the RTP system. Gamma analysis showed a passing rate of 93% for 5% dose and 2mm DTA scoring criteria. Both relative and absolute dose profiles are in good agreement, except in the peripheral beamlets where the gel measured slightly higher dose, possibly because of the changing head scatter conditions that the RTP is not fully accounting for. Our results have also been benchmarked against ionization chamber measurements. Conclusion: We have investigated the use of a polymer gel for the 3D dosimetric characterization and evaluation of GRID therapy. Our results demonstrated that the planning system can predict fairly accurately the dose distribution for GRID type therapy.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

Sci-Thur PM – Colourful Interactions: Highlights 01: Design to delivery of spatially fractionated mini-beam canine radiotherapy

Spatial fractionation of radiation using arrays of narrow parallel micro-planar beams (less than 1 mm), is a relatively new concept with many unknowns specifically within the underlying biology of cell death. A tungsten collimator has been designed to produce mini-beams with a Varian linear accelerator for translational animal research into the effectiveness of spatial fractionation mini-beam radiotherapy (MBRT). This work presents the treatment planning process and workflow for the application of MBRT treatments within a clinical study. For patient dose calculations, the MBRT collimator was incorporated into a Monte Carlo based treatment planning system called MMCTP. Treatment planning was split between Eclipse and MMCTP, as the field apertures were determined within Eclipse prior to being sent to MMCTP for dose calculations. The calculated plan was transferred back into Aria with updated MUs per field for patient treatment. Patients were positioned within a vac-lock bag lying prone with a bite block and a thermoplastic mask to immobilize the head. Prior to treatment, a delivery verification plan was created within MMCTP. DQA output measurements of the treatment fields agreed with the calculated dose to within 1.5%. We have presented a workflow for MBRT treatments that include the planning technique, dose calculation method, DQA process and data integration into a record and verify system. The clinical study following this workflow represent the first series of linac based MBRT patients and depending on the clinical outcome of the study, our technique could be applied to human MBRT treatments.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Single-colony MALDI mass spectrometry imaging reveals spatial differences in metabolite abundance between natural and cultured Trichodesmium morphotypes

Trichodesmium, a globally significant N 2 -fixing marine cyanobacterium, forms extensive surface blooms in nutrient-poor ocean regions. These blooms consist of a dynamic assemblage of Trichodesmium species that form distinct colony morphotypes and are inhabited by diverse microorganisms. Trichodesmium colony morphotypes vary in ecological niche, nutrient uptake, and organic molecule release, differentially impacting ocean carbon and nitrogen biogeochemical cycles. Here, we assessed the poorly studied spatial abundance of metabolites within and between three morphologically distinct Trichodesmium colonies collected from the Red Sea. We also compared these results with two morphotypes of the cultivable Trichodesmium strain IMS101. Using matrix-assisted laser desorption/ionization (MALDI) mass spectrometry imaging (MSI) coupled with liquid extraction surface analysis (LESA) tandem mass spectrometry (MS2), we identified and localized a wide range of small metabolites associated with single-colony Trichodesmium morphotypes. Our untargeted MALDI-MSI approach revealed 80 unique features (metabolites) shared between Trichodesmium morphotypes. Discrimination analysis showed spatial variations in 57 shared metabolites, accounting for 62% of the observed variation between morphotypes. The greatest variations in metabolite abundance were observed between the cultured morphotypes compared to the natural colony morphotypes, suggesting substantial differences in metabolite production between the cultivable strain IMS101 and the naturally occurring colony morphotypes that the cultivable strain is meant to represent. This study highlights the variations in metabolite abundance between natural and cultured Trichodesmium morphotypes and provides valuable insights into metabolites common to morphologically distinct Trichodesmium colonies, offering a foundation for future targeted metabolomic investigations.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2017

Effect of spatial nonuniformity of heating on compression and burning of a thermonuclear target under direct multibeam irradiation by a megajoule laser pulse

Direct-drive fusion targets are considered at present as an alternative to targets of indirect compression at a laser energy level of about 2 MJ. In this approach, the symmetry of compression and ignition of thermonuclear fuel play the major role. We report on the results of theoretical investigation of compression and burning of spherical direct-drive targets in the conditions of spatial nonuniformity of heating associated with a shift of the target from the beam center of focusing and possible laser radiation energy disbalance in the beams. The investigation involves numerous calculations based on a complex of 1D and 2D codes RAPID, SEND (for determining the target illumination and the dynamics of absorption), DIANA, and NUT (1D and multidimensional hydrodynamics of compression and burning of targets). The target under investigation had the form of a two-layer shell (ablator made of inertial material CH and DT ice) filled with DT gas. We have determined the range of admissible variation of compression and combustion parameters of the target depending on the variation of the spatial nonuniformity of its heating by a multibeam laser system. It has been shown that low-mode (long-wavelength) perturbations deteriorate the characteristics of the central region due to less effective conversion of the kinetic energy of the target shell into the internal energy of the center. Local initiation of burning is also observed in off-center regions of the target in the case of substantial asymmetry of irradiation. In this case, burning is not spread over the entire volume of the DT fuel as a rule, which considerably reduces the thermonuclear yield as compared to that in the case of spherical symmetry and central ignition.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2015

Structure of the spatial periphery of the isotopes {sup 9,11}Li

The cross sections for the (t, p) reactions on the lithium isotopes {sup 9,11}Li were calculated within a theoretical approach based on employing integral equations of the four-body problem in the Alt—Grassberger-Sandhas formalism and the multiparticle shell model. This made it possible to determine the wave functions for the relative motion of various clusters and the nuclear core and to calculate, on their basis, the root-mean-square radii of nuclei of the isotopes {sup 9,11}Li and the spatial structure of their neutron periphery. It is shown that the {sup 9}Li nucleus has virtually no neutron halo. The {sup 11}Li nucleus is a Borromean halo nucleus. The two-neutron periphery of this nucleus manifests itself in both spatial configurations, a dineutron and a cigar one, the respective root-mean-square radii being large (about 6.5 to 6.9 fm)

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2015

Binding energy of excitons formed from spatially separated electrons and holes in insulating quantum dots

It is found that the binding energy of the ground state of an exciton formed from an electron and a hole spatially separated from each other (the hole is moving within a quantum dot, and the electron is localized above the spherical (quantum dot)–(insulating matrix) interface) in a nanosystem containing insulating Al{sub 2}O{sub 3} quantum dots is substantially increased (by nearly two orders of magnitude) compared to the exciton binding energy in an Al{sub 2}O{sub 3} single crystal. It is established that, in the band gap of an Al{sub 2}O{sub 3} nanoparticle, a band of exciton states (formed from spatially separated electrons and holes) appears. It is shown that there exists the possibility of experimentally detecting the ground and excited exciton states in the band gap of Al{sub 2}O{sub 3} nanoparticles at room temperature from the absorption spectrum of the nanosystem.

36 MATERIALS SCIENCE↗
DOE OSTI2015

Spatial hole burning and spectral stability of a quantum-dot laser

The inhomogeneous intensity distribution of the optical model along the axis of a semiconductor quantum-dot laser results in spatial hole burning. The influence of this phenomenon on the stability of the multifrequency emission spectrum is studied when the optical transition of the quantum dots is characterized by considerable homogeneous broadening. The results of two models—in which inhomogeneous broadening is disregarded and taken into account—regarding the stability of the radiation spectrum under the influence of slight variation of the spectral loss dependence in the resonator are compared. Inhomogeneous distribution of the charge carriers (spatial hole burning) is found to be a critical factor in determining the form and stability of the spectrum.

36 MATERIALS SCIENCE↗
DOE OSTI2015

Spatially correlated two-dimensional arrays of semiconductor and metal quantum dots in GaAs-based heterostructures

A single molecular-beam epitaxy process is used to produce GaAs-based heterostructures containing two-dimensional arrays of InAs semiconductor quantum dots and AsSb metal quantum dots. The twodimensional array of AsSb metal quantum dots is formed by low-temperature epitaxy which provides a large excess of arsenic in the epitaxial GaAs layer. During the growth of subsequent layers at a higher temperature, excess arsenic forms nanoinclusions, i.e., metal quantum dots in the GaAs matrix. The two-dimensional array of such metal quantum dots is created by the δ doping of a low-temperature GaAs layer with antimony which serves as a precursor for the heterogeneous nucleation of metal quantum dots and accumulates in them with the formation of AsSb metal alloy. The two-dimensional array of InAs semiconductor quantum dots is formed via the Stranski–Krastanov mechanism at the GaAs surface. Between the arrays of metal and semiconductor quantum dots, a 3-nm-thick AlAs barrier layer is grown. The total spacing between the arrays of metal and semiconductor quantum dots is 10 nm. Electron microscopy of the structure shows that the arrangement of metal quantum dots and semiconductor quantum dots in the two-dimensional arrays is spatially correlated. The spatial correlation is apparently caused by elastic strain and stress fields produced by both AsSb metal and InAs semiconductor quantum dots in the GaAs matrix.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Dynamics of Spatially Inhomogeneous Spin Polarization of Nonequilibrium Conduction Electrons in Magnetic Transitions

The equation of the dynamics of the magnetic moment motion that has been averaged over the ensemble of nonequilibrium spin-injected electrons in a ferromagnetic transition in the presence of exchange interaction, interaction with an external electromagnetic field, and a thermostat has been obtained taking into account the spatial inhomogeneity of the charge carrier distribution. It has been shown that taking into account the spatial inhomogeneity of the charge carrier distribution in the equation of the dynamics of the magnetic moment motion allows for describing the various processes of electron transfer in the magnetic transition. The probability of quantum transitions of electrons with opposite spin directions, which determine spin relaxation in interaction with a thermostat, has been estimated. It has been shown that the anisotropy of the radiation medium is determined not only by the anisotropy of the sd-exchange tensor, but also by the additional anisotropy that is caused by the electron impulse derivatives of this tensor. The considered phenomena have a great potential for the detection of new effects and development of new devices based on them, including compact tunable radiation sources in the terahertz frequency range, which is obviously difficult to generate.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

Spatially resolved characterization of optical and recombination losses for different industrial silicon solar cell architectures

In this work, spatially resolved characterization methods are used to identify loss mechanisms for common p -type silicon solar cell architectures, including multicrystalline aluminum back surface field (Al-BSF), monocrystalline Al-BSF, monocrystalline passivated emitter and rear cells (PERC), and bifacial monocrystalline PERC. The characterization methods used in this work include suns-V OC , photoluminescence imaging, and spatially resolved external quantum efficiency and reflectance measurements. The optical and recombination losses are driven by the material properties, cell processing conditions, and device architecture. These losses are quantified and categorized in terms of underlying mechanisms (e.g., front reflectance, escape reflectance, front recombination, and parasitic optical absorption and recombination in the bulk and rear). The ability to create images of these loss parameters can be used to gain more insight into the materials and manufacturing processes used to produce solar cells, and examples are given in this work to illustrate how these images can help reveal the origin of defects.

14 SOLAR ENERGY↗
DOE OSTI2020

Spatial and Temporal Characterization of Polarization Entanglement

We describe the full temporal and spatial characterization of polarization-entangled photons produced by Spontaneous Parametric Down Conversions using an intensified high-speed optical camera, Tpx3Cam. This novel technique allows for precise determination of Bell inequality parameters and for new characterization methods for the spatial distribution of entangled quantum information. We also discuss a technique to synchronize multiple cameras separated by vast distances, which will be required for a distributed quantum network.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Scaling Resolution of Gigapixel Whole Slide Images Using Spatial Decomposition on Convolutional Neural Networks

Gigapixel images are prevalent in scientific domains ranging from remote sensing, and satellite imagery to microscopy, etc. However, training a deep learning model at the natural resolution of those images has been a challenge in terms of both, overcoming the resource limit (e.g. HBM memory constraints), as well as scaling up to a large number of GPUs. In this paper, we trained Residual neural Networks (ResNet) on 22,528 x 22,528-pixel size images using a distributed spatial decomposition method on 2,304 GPUs on the Summit Supercomputer. We applied our method on a Whole Slide Imaging (WSI) dataset from The Cancer Genome Atlas (TCGA) database. WSI images can be in the size of 100,000 x 100,000 pixels or even larger, and in this work we studied the effect of image resolution on a classification task, while achieving state-of-the-art AUC scores. Moreover, our approach doesn't need pixel-level labels, since we're avoiding patching from the WSI images completely, while adding the capability of training arbitrary large-size images. This is achieved through a distributed spatial decomposition method, by leveraging the non-block fat-tree interconnect network of the Summit architecture, which enabled GPU-to-GPU direct communication. Finally, detailed performance analysis results are shown, as well as a comparison with a data-parallel approach when possible.

Tsaris, Aristeidis (aris)↗
DOE OSTI2025

CareWELL: Multimodal Region Representation Learning with Spatial Contexts for Urban Health

Rapid urbanization affects living environments by intensifying exposure to air pollution, heat, noise, and urban dynamics, which together contribute to uneven health outcomes across neighborhoods. For instance, cardiovascular, respiratory, and mental health conditions are each influenced by distinct exposures such as air pollution, extreme temperatures, or limited access to green space. These heterogeneous patterns require understanding the characteristics of geographic regions in order to explain why urban health risks vary across urban areas. Recent work in self-supervised region representation learning provides a promising way to model such characteristics from multimodal geospatial data. However, existing methods face two major limitations: (i) they often depend on non-public datasets, limiting reproducibility and applicability, and (ii) their generic pretraining objectives overlook health-relevant determinants, including temporal variability in environmental exposures and inequalities in social conditions. To address these gaps, we propose Context-Aware Region rEpresentation with Weather, Environment, and Location Learning (CareWELL). CareWELL leverages large language models to encode seasonal variability in weather, employs contrastive learning to align geo-coordinate and weather representations, and introduces a context-aware objective that integrates socio-demographic factors while preserving spatial correlations. We evaluate CareWELL by predicting six urban health outcomes in Manhattan, New York City, and demonstrate that CareWELL consistently outperforms state-of-the-art baselines as well as a traditional spatial computing method. These results suggest the importance of context-aware pretraining objectives for learning health-relevant region representations.

Namgung, Min [ORNL]↗
DOE OSTI2026

Spatially Accelerated Winding Numbers for Curved Geometry

The generalized winding number (GWN) is a scalar field that supports robust containment queries on curved geometry, including non-watertight, overlapping, and nested boundary representations. While queries can be easily parallelized over samples, direct evaluation on parametric curves and surfaces remains costly for large and complex models. Fast, state-of-the-art GWN approaches leverage a spatial index to approximate the GWN, typically coupled with a Taylor expansion which approximates the GWN contribution for far clusters of geometric primitives. However, such methods operate only on discrete inputs such as triangle meshes and point clouds, and would introduce containment errors near boundaries if applied to curved input. We extend support for fast GWN evaluation over arbitrary collections of NURBS curves in 2D and trimmed NURBS patches in 3D via a Bounding Volume Hierarchy that stores efficiently precomputed moment data in the hierarchy nodes. When querying the hierarchy, approximations for far clusters are used alongside direct evaluation for nearby NURBS primitives, achieving sub-linear complexity while preserving the geometric features in the vicinity of the query point. Central to our performance improvements is an adaptive subdivision strategy for NURBS primitives during a preprocessing phase, creating better spatial partitions while retaining the same accuracy for containment decisions as a direct evaluation. We demonstrate the performance and accuracy of our approach across a large collection of 2D and 3D datasets.

Computer science↗
DOE OSTI2023

Spatial Environmental Assessment Tool (SEAT)

SAND2024-08551O The Spatial Environmental Assessment Tool (SEAT) evaluates potential environmental risk associated with marine energy device deployment by coupling modeled impacts with risk severity maps. As a graphical user interface-based software, it interacts with marine energy stressor and receptor data to evaluate the risk of changes to marine environment. SEAT, which relies on spatial and temporal data, is a plug-in for geospatial software QGIS. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Chartrand, Chris↗
DOE OSTI2024

Spatially Local Surrogate Modeling of Subgrid-Scale Effects in Idealized Atmospheric Flows: A Deep Learned Approach Using High-Resolution Simulation Data

Abstract We introduce a machine learned surrogate model from high-resolution simulation data to capture the subgrid-scale effects in dry, stratified atmospheric flows. We use deep neural networks (NNs) to model the spatially local state differences between a coarse-resolution simulation and a high-resolution simulation. The setup enables the capture of both dissipative and antidissipative effects in the state differences. The NN model is able to accurately capture the state differences in offline tests outside the training regime. In online tests intended for production use, the NN-coupled coarse simulation has higher accuracy over a significant period of time compared to the coarse-resolution simulation without any correction. We provide evidence of the capability of the NN model to accurately capture high-gradient regions in the flow field. With the accumulation of the errors, the NN-coupled simulation becomes computationally unstable after approximately 90 coarse simulation time steps. Insights gained from these surrogate models further pave the way for formulating stable, complex, physics-based spatially local NN models which are driven by traditional subgrid-scale turbulence closure models. Significance Statement Flows in the atmosphere are highly chaotic and turbulent, comprising flow structures of broad scales. For effective computational modeling of atmospheric flows, the effects of the small- and large-scale structures need to be captured by the simulations. Capturing the small-scale structures requires fine-resolution simulations. Even with the current state-of-the-art supercomputers, it can be prohibitively expensive to simulate these flows when computed for the entire earth over climate time scales. Thus, it is necessary to focus on the larger-scale structures using a coarse-resolution simulation while capturing the effects of the smaller-scale structures using some parameterization (approximation) scheme and incorporating it into the coarse-resolution simulation. We use machine learning to model the effects of the small-scale structures (subgrid-scale effects) in atmospheric flows. Data from a fine-resolution simulation is used to compute the missing subgrid-scale effects in coarse-resolution simulations. We then use machine learning models to approximate these differences between the coarse- and fine-resolution simulations. We see improved accuracy for the coarse-resolution simulations when corrected using these machine learned models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Global Precipitation Trends across Spatial Scales Using Satellite Observations

Little dispute surrounds the observed global temperature changes over the past decades. As a result, there is widespread agreement that a corresponding response in the global hydrologic cycle must exist. However, exactly how such a response manifests remains unsettled. Here we use a unique recently developed long-term satellite-based record to assess changes in precipitation across spatial scales. We show that warm climate regions exhibit decreasing precipitation trends, while arid and polar climate regions show increasing trends. At the country scale, precipitation seems to have increased in 96 countries, and decreased in 104. We also explore precipitation changes over 237 global major basins. Our results show opposing trends at different scales, highlighting the importance of spatial scale in trend analysis. Furthermore, while the increasing global temperature trend is apparent in observations, the same cannot be said for the global precipitation trend according to the high-resolution dataset, PERSIANN-CDR, used in this study.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Spatial Variability of Winds and HRRR–NCEP Model Error Statistics at Three Doppler-Lidar Sites in the Wind-Energy Generation Region of the Columbia River Basin

Annually and seasonally averaged wind profiles from three Doppler lidars were gathered from sites in the Columbia River basin of east-central Oregon and Washington, a major region of wind-energy production, for the Second Wind Forecast Improvement Project (WFIP2) experiment. The profile data are used to quantify the spatial variability of wind flows in this area of complex terrain, to assess the HRRR-NCEP model's ability to capture spatial and temporal variability of wind profiles, and to evaluate model errors. Annually averaged measured wind speed differences over the 70-km extent of the lidar measurements reached 1 m s -1 within the wind-turbine rotor layer, and 2 m s -1 for 200-500 m AGL. Stronger wind speeds in the lowest 500 m occurred at sites higher in elevation, farther from the river, and farther west - closer to the Cascade Mountain barrier. Validating against the lidar data, the HRRR model underestimated strong wind speeds (>12 m s -1 ) and, consequently, their frequency of occurrence, especially at the two lowest-elevation sites, producing annual low biases in rotor-layer wind speed of 0.5 m s -1 . The RMSE between measured and modeled winds at all sites was about 3 m s -1 and did not degrade significantly with forecast lead time. The nature of the model errors was different for different seasons. Furthermore, although the three sites were located in the same basin terrain, the nature of the model errors was different at each site. Thus, if only one of the sites had been instrumented, different conclusions would have been drawn as to the major sources of model error, depending on where the measurements were made.

17 WIND ENERGY↗