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All sourcesNASA NTRSDOE OSTI
NASA NTRS2018

Risk-Based Explosion Assessment Internal Explosion of Exploration Upper Stage in Vehicle Assembly Building

This paper presents risk-based explosion analyses used to determine if an explosion of NASA's Space Launch System (SLS) Exploration Upper Stage (EUS) during fueling in Vehicle Assembly Building (VAB) High Bay 4 can hazard the Space Launch System (SLS) being processed in Bay 3. This paper focuses on blast fragmentation as it was the controlling hazard. An estimate of the amount of Net Explosion Weight (NEW) was used to develop a fragment list (mass, shape, takeoff velocity/angle) given an explosion occurs at ground level in Bay 4. Intervening superstructure that exists between Bay 4 and Bay 3 (that could potentially block EUS fragments) was modeled based on detailed visual images (VISSIM) and AUTOCAD/structural drawings. The fragment list was input to a 3D trajectory application that performs multiple random explosion simulations; each simulation varying fragment ballistic coefficient and takeoff angle/velocity. Individual fragments are tracked until stopped by the intervening superstructure or reach Bay 3, potentially impacting the SLS. The probability of impacting the SLS is then determined from the random simulations; the results are used to help decision-makers determine the efficacy of co-processing within the VAB and decide what mitigations may be appropriate.

Explosion Assessment↗
NASA NTRS2023

Observations of Typhoon Generated Gravity Waves From the CIPS and AIRS Instruments and Comparison to the High-Resolution ECMWF Model

The satellite-based Cloud Imaging and Particle Size (CIPS) instrument and Atmospheric Infrared Sounder (AIRS) observed concentric gravity waves (GWs) generated by Typhoon Yutu in late October 2018. This work compares CIPS and AIRS nadir viewing observations of GWs at altitudes of 50–55 and 30–40 km, respectively, to simulations from the high-resolution European Centre for Medium-Range Weather Forecasting Integrated Forecasting System (ECMWF-IFS) and ECMWF reanalysis v5 (ERA5). Both ECMWF-IFS with 9 km and ERA5 with 31 km horizontal resolution show concentric GWs at similar locations and timing as the AIRS and CIPS observations. The GW wavelengths are ∼225–236 km in ECMWF-IFS simulations, which compares well with the wavelength inferred from the observations. After validation of ECMWF GWs, five category five typhoon events during 2018 are analyzed using ECMWF to obtain characteristics of concentric GWs in the Western Pacific regions. The amplitudes of GWs in the stratosphere are not strongly correlated with the strength of typhoons, but are controlled by background wind conditions. Our results confirm that amplitudes and shapes of concentric GWs observed in the stratosphere and lowermost mesosphere are heavily influenced by the background wind conditions.

gravity wave↗
DOE OSTI2017

Improved image of intrusive bodies at Newberry Volcano, Oregon, based on 3D gravity modelling

Beneath Newberry Volcano is one of the largest geothermal heat reservoirs in the western United States and it has been extensively studied for the last 40 years. Several magmatic intrusions have been recognized at depths between 2.5 and 8 km and some of them identified as suitable targets for enhanced geothermal energy and tested during two previous EGS campaigns. These subsurface structures have been intersected by three deep wells and imaged by various geophysical methods including seismic tomography and magnetotellurics. Although three high quality gravity surveys were completed between 2006 and 2010 as part of various projects, a complete synthesis and interpretation of the gravity data has not yet been performed. Regional gravity data also exist in the vicinity of the Newberry volcano and have been added to these surveys to constitute a dataset with a total of 1418 gravity measurements. When coupled with existing geologic and geophysical data and models, this new gravity dataset provides important constraints on the depth and contours of the magmatic bodies previously identified by other methods and thus greatly contributing to facilitate any future drilling and stimulation works. Using the initial structures discovered by seismic tomography, inversion of gravity data has been performed. Shape, density values and depths of various bodies were allowed to vary and three main bodies have been identified. Densities of the middle and lower intrusive bodies (~2.6-2.7 g/cm3) are consistent with rhyolite, basalt or granites. Modeled density of the near-surface caldera body match that of a low density tephra material and the density of the shallow ring structures contained in the upper kilometer correspond to that of welded tuff or low-density rhyolites. Modeled bodies are in reality a composite of thin layers; however, average densities of the modeled gravity bodies are in good agreement with the density log obtained in one well located on the western flank (well 55-29). Final gravity data residuals show that most of the observed gravity anomalies at the surface can be explained by the modeled gravity bodies and are consistent with other site characterization information.

Cascade Range↗
NASA NTRS2017

Imaging a Free-Geometry Magma Reservoir Using FEM-Based Linear Inverse Modeling of InSAR Data: Application to Rabaul Caldera, Papua New Guinea

We test an innovative inversion scheme using Green’s functions from an array of pressure sources embedded in finite-element method (FEM) models to image, without assuming an a-priori geometry, the composite and complex shape of a volcano deformation source. We invert interferometric synthetic aperture radar (InSAR) data to estimate the pressurization and shape of the magma reservoir of Rabaul caldera, Papua New Guinea. The results image the extended shallow magmatic system responsible for a broad and long-term subsidence of the caldera between 2007 February and 2010 December. Elastic FEM solutions are integrated into the regularized linear inversion of InSAR data of volcano surface displacements in order to obtain a 3-D image of the source of deformation. The Green’s function matrix is constructed from a library of forward line-of-sight displacement solutions for a grid of cubic elementary deformation sources. Each source is sequentially generated by removing the corresponding cubic elements from a common meshed domain and simulating the injection of a fluid mass flux into the cavity, which results in a pressurization and volumetric change of the fluidfilled cavity. The use of a single mesh for the generation of all FEM models avoids the computationally expensive process of non-linear inversion and remeshing a variable geometry domain. Without assuming an a-priori source geometry other than the configuration of the 3-D grid that generates the library of Green’s functions, the geodetic data dictate the geometry of the magma reservoir as a 3-D distribution of pressure (or flux of magma) within the source array. The inversion of InSAR data of Rabaul caldera shows a distribution of interconnected sources forming an amorphous, shallow magmatic system elongated under two opposite sides of the caldera. The marginal areas at the sides of the imaged magmatic system are the possible feeding reservoirs of the ongoing Tavurvur volcano eruption of andesitic products on the east side and of the past Vulcan volcano eruptions of more evolved materials on the west side. The interconnection and spatial distributions of sources correspond to the petrography of the volcanic products described in the literature and to the dynamics of the single and twin eruptions that characterize the caldera. The ability to image the complex geometry of deformation sources in both space and time can improve our ability to monitor active volcanoes, widen our understanding of the dynamics of active volcanic systems and improve the predictions of eruptions.

Inverse theory↗
DOE OSTI2020

Lipids status and copper in a single astrocyte of the rat model for amyotrophic lateral sclerosis: Correlative synchrotron-based X-ray and infrared imaging

Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease, causing death of motor neurons controlling voluntary muscles. The pathological mechanisms of the disease are only partially understood. The hSOD1-G93A ALS rat model is characterized by an overexpression of human mutated SOD1, causing increased vulnerability by forming intracellular protein aggregates, inducing excitotoxicity, affecting oxidative balance and disturbing axonal transport. In this study we followed the bio-macromolecular organic composition and compartmentalization together with trace metal distribution in situ in single astrocytes from the ALS rat model and compared them to the control astrocytes from nontransgenic littermates by simultaneous use of two synchrotron radiation-based methods: Fourier transform infrared microspectroscopy (SRFTIR) and hard X-ray fluorescence microscopy (XRF). Here we show that ALS cells contained more Cu, which colocalized with total lipids, increased carbonyl groups and oxidized lipids, thus implying direct involvement of Cu in oxidative stress of lipidic components without direct connection to protein aggregation in situ.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Generative attribute optimization

A generative attribute optimization (“GAO”) system facilitates understanding of effects of changes of attribute values of an object on a characteristic of the object and automatically identifying attribute values to achieve a desired result for the characteristic. The GAO system trains a generator (encoder and decoder) using an attribute generative adversarial network. The GAO model includes the trained generator and a separately trained predictor model. The GAO model inputs an input image and modified attribute values and employs the encoder and the decoder to generate a modified image that is the input image modified based on the modified attribute values. The GAO model then employs the predictor model to that inputs the modified image and generate a prediction of a characteristic of the modified image. The GAO system may employ an optimizer to modify the attribute values until an objective based on the desired result is achieved.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1990

Intensity dependent spread theory

The Intensity Dependent Spread (IDS) procedure is an image-processing technique based on a model of the processing which occurs in the human visual system. IDS processing is relevant to many aspects of machine vision and image processing. For quantum limited images, it produces an ideal trade-off between spatial resolution and noise averaging, performs edge enhancement thus requiring only mean-crossing detection for the subsequent extraction of scene edges, and yields edge responses whose amplitudes are independent of scene illumination, depending only upon the ratio of the reflectance on the two sides of the edge. These properties suggest that the IDS process may provide significant bandwidth reduction while losing only minimal scene information when used as a preprocessor at or near the image plane.

Holben, Richard↗
NASA NTRS2011

Constraining the Absolute Orientation of eta Carinae's Binary Orbit: A 3-D Dynamical Model for the Broad [Fe III] Emission

We present a three-dimensional (3-D) dynamical model for the broad [Fe III] emission observed in Eta Carinae using the Hubble Space Telescope/Space Telescope Imaging Spectrograph (HST/STIS). This model is based on full 3-D Smoothed Particle Hydrodynamics (SPH) simulations of Eta Car's binary colliding winds. Radiative transfer codes are used to generate synthetic spectro-images of [Fe III] emission line structures at various observed orbital phases and STIS slit position angles (PAs). Through a parameter study that varies the orbital inclination i, the PA(theta) that the orbital plane projection of the line-of-sight makes with the apastron side of the semi-major axis, and the PA on the sky of the orbital axis, we are able, for the first time, to tightly constrain the absolute 3-D orientation of the binary orbit. To simultaneously reproduce the blue-shifted emission arcs observed at orbital phase 0.976, STIS slit PA = +38deg, and the temporal variations in emission seen at negative slit PAs, the binary needs to have an i approx. = 130deg to 145deg, Theta approx. = -15deg to +30deg, and an orbital axis projected on the sky at a P A approx. = 302deg to 327deg east of north. This represents a system with an orbital axis that is closely aligned with the inferred polar axis of the Homunculus nebula, in 3-D. The companion star, Eta(sub B), thus orbits clockwise on the sky and is on the observer's side of the system at apastron. This orientation has important implications for theories for the formation of the Homunculus and helps lay the groundwork for orbital modeling to determine the stellar masses.

Madura, T. I.↗
DOE OSTI2015

TU-G-204-06: Correlation Between Texture Analysis-Based Model Observer and Human Observer in Diagnosis of Ischemic Infarct in Non-Contrast Head CT of Adults

Purpose: To investigate the correlation between texture analysis-based model observer and human observer in the task of diagnosis of ischemic infarct in non-contrast head CT of adults. Methods: Non-contrast head CTs of five patients (2 M, 3 F; 58–83 y) with ischemic infarcts were retro-reconstructed using FBP and Adaptive Statistical Iterative Reconstruction (ASIR) of various levels (10–100%). Six neuro -radiologists reviewed each image and scored image quality for diagnosing acute infarcts by a 9-point Likert scale in a blinded test. These scores were averaged across the observers to produce the average human observer responses. The chief neuro-radiologist placed multiple ROIs over the infarcts. These ROIs were entered into a texture analysis software package. Forty-two features per image, including 11 GLRL, 5 GLCM, 4 GLGM, 9 Laws, and 13 2-D features, were computed and averaged over the images per dataset. The Fisher-coefficient (ratio of between-class variance to in-class variance) was calculated for each feature to identify the most discriminating features from each matrix that separate the different confidence scores most efficiently. The 15 features with the highest Fisher -coefficient were entered into linear multivariate regression for iterative modeling. Results: Multivariate regression analysis resulted in the best prediction model of the confidence scores after three iterations (df=11, F=11.7, p-value<0.0001). The model predicted scores and human observers were highly correlated (R=0.88, R-sq=0.77). The root-mean-square and maximal residual were 0.21 and 0.44, respectively. The residual scatter plot appeared random, symmetric, and unbiased. Conclusion: For diagnosis of ischemic infarct in non-contrast head CT in adults, the predicted image quality scores from texture analysis-based model observer was highly correlated with that of human observers for various noise levels. Texture-based model observer can characterize image quality of low contrast, subtle texture changes in addition to human observers.

60 APPLIED LIFE SCIENCES↗
NASA NTRS2006

Reducing Centroid Error Through Model-Based Noise Reduction

A method of processing the digitized output of a charge-coupled device (CCD) image detector has been devised to enable reduction of the error in computed centroid of the image of a point source of light. The method involves model-based estimation of, and correction for, the contributions of bias and noise to the image data. The method could be used to advantage in any of a variety of applications in which there are requirements for measuring precise locations of, and/or precisely aiming optical instruments toward, point light sources. In the present method, prior to normal operations of the CCD, one measures the point-spread function (PSF) of the telescope or other optical system used to project images on the CCD. The PSF is used to construct a database of spot models representing the nominal CCD pixel outputs for a point light source projected onto the CCD at various positions incremented by small fractions of a pixel.

Lee, Shinhak↗
DOE OSTI2020

Super resolution for root imaging

Premise High‐resolution cameras are very helpful for plant phenotyping as their images enable tasks such as target vs. background discrimination and the measurement and analysis of fine above‐ground plant attributes. However, the acquisition of high‐resolution images of plant roots is more challenging than above‐ground data collection. An effective super‐resolution (SR) algorithm is therefore needed for overcoming the resolution limitations of sensors, reducing storage space requirements, and boosting the performance of subsequent analyses. Methods We propose an SR framework for enhancing images of plant roots using convolutional neural networks. We compare three alternatives for training the SR model: (i) training with non‐plant‐root images, (ii) training with plant‐root images, and (iii) pretraining the model with non‐plant‐root images and fine‐tuning with plant‐root images. The architectures of the SR models were based on two state‐of‐the‐art deep learning approaches: a fast SR convolutional neural network and an SR generative adversarial network. Results In our experiments, we observed that the SR models improved the quality of low‐resolution images of plant roots in an unseen data set in terms of the signal‐to‐noise ratio. We used a collection of publicly available data sets to demonstrate that the SR models outperform the basic bicubic interpolation, even when trained with non‐root data sets. Discussion The incorporation of a deep learning–based SR model in the imaging process enhances the quality of low‐resolution images of plant roots. We demonstrate that SR preprocessing boosts the performance of a machine learning system trained to separate plant roots from their background. Our segmentation experiments also show that high performance on this task can be achieved independently of the signal‐to‐noise ratio. We therefore conclude that the quality of the image enhancement depends on the desired application.

Ruiz‐Munoz, Jose F.↗
DOE OSTI2018

Superresolution Diffuse Optical Imaging by Localization of Fluorescence

The multiple scattering of light presents major challenges in realizing useful in vivo imaging at tissue depths of more than about one millimeter, where many answers to health questions lie. Visible through near-infrared photons can be readily and safely detected through centimeters of tissue; however, limited information is available for image formation. One strategy for obtaining images is to model the photon transport and a simple incoherent model is the diffusion equation approximation to the Boltzmann transport equation. Such an approach provides a prediction of the mean intensity of heavily scattered light and hence provides a forward model for optimization-based computational imaging. While diffuse optical imaging methods have received substantial attention, they remain restricted in terms of resolution because of the loss of high-spatial-frequency information that is associated with the multiple scattering of photons. Consequently, only relatively large inhomogeneities, such as tumors or organs in small animals, can be effectively resolved. We introduce a superresolution imaging approach based on point localization in a diffusion framework that enables over two orders of magnitude improvement in the spatial resolution of diffuse optical imaging. The method is demonstrated experimentally by localizing a fluorescent inhomogeneity in a highly scattering slab and characterizing the localization uncertainty. The approach allows imaging through centimeters of tissue with a resolution of tens of microns, thereby enabling cells or cell clusters to be resolved. More generally, this high-resolution imaging approach could be applied with any physical transport or wave model and hence to a broad class of physical problems. Finally, paired with a suitable optical contrast mechanism, as can be realized with targeted fluorescent molecules or genetically modified animals, superresolution diffuse imaging should open alternative dimensions for in vivo applications.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

Large area CMOS active pixel sensor x-ray imager for digital breast tomosynthesis: Analysis, modeling, and characterization

Purpose: Large area x-ray imagers based on complementary metal-oxide-semiconductor (CMOS) active pixel sensor (APS) technology have been proposed for various medical imaging applications including digital breast tomosynthesis (DBT). The low electronic noise (50–300 e{sup −}) of CMOS APS x-ray imagers provides a possible route to shrink the pixel pitch to smaller than 75 μm for microcalcification detection and possible reduction of the DBT mean glandular dose (MGD). Methods: In this study, imaging performance of a large area (29 × 23 cm{sup 2}) CMOS APS x-ray imager [Dexela 2923 MAM (PerkinElmer, London)] with a pixel pitch of 75 μm was characterized and modeled. The authors developed a cascaded system model for CMOS APS x-ray imagers using both a broadband x-ray radiation and monochromatic synchrotron radiation. The experimental data including modulation transfer function, noise power spectrum, and detective quantum efficiency (DQE) were theoretically described using the proposed cascaded system model with satisfactory consistency to experimental results. Both high full well and low full well (LFW) modes of the Dexela 2923 MAM CMOS APS x-ray imager were characterized and modeled. The cascaded system analysis results were further used to extract the contrast-to-noise ratio (CNR) for microcalcifications with sizes of 165–400 μm at various MGDs. The impact of electronic noise on CNR was also evaluated. Results: The LFW mode shows better DQE at low air kerma (K{sub a} < 10 μGy) and should be used for DBT. At current DBT applications, air kerma (K{sub a} ∼ 10 μGy, broadband radiation of 28 kVp), DQE of more than 0.7 and ∼0.3 was achieved using the LFW mode at spatial frequency of 0.5 line pairs per millimeter (lp/mm) and Nyquist frequency ∼6.7 lp/mm, respectively. It is shown that microcalcifications of 165–400 μm in size can be resolved using a MGD range of 0.3–1 mGy, respectively. In comparison to a General Electric GEN2 prototype DBT system (at MGD of 2.5 mGy), an increased CNR (by ∼10) for microcalcifications was observed using the Dexela 2923 MAM CMOS APS x-ray imager at a lower MGD (2.0 mGy). Conclusions: The Dexela 2923 MAM CMOS APS x-ray imager is capable to achieve a high imaging performance at spatial frequencies up to 6.7 lp/mm. Microcalcifications of 165 μm are distinguishable based on reported data and their modeling results due to the small pixel pitch of 75 μm. At the same time, potential dose reduction is expected using the studied CMOS APS x-ray imager.

60 APPLIED LIFE SCIENCES↗
NASA NTRS2016

Derivation and Validation of Supraglacial Lake Volumes on the Greenland Ice Sheet from High-Resolution Satellite Imagery

Supraglacial meltwater lakes on the western Greenland Ice Sheet (GrIS) are critical components of its surface hydrology and surface mass balance, and they also affect its ice dynamics. Estimates of lake volume, however, are limited by the availability of in situ measurements of water depth,which in turn also limits the assessment of remotely sensed lake depths. Given the logistical difficulty of collecting physical bathymetric measurements, methods relying upon in situ data are generally restricted to small areas and thus their application to largescale studies is difficult to validate. Here, we produce and validate spaceborne estimates of supraglacial lake volumes across a relatively large area (1250 km(exp 2) of west Greenland's ablation region using data acquired by the WorldView-2 (WV-2) sensor, making use of both its stereo-imaging capability and its meter-scale resolution. We employ spectrally-derived depth retrieval models, which are either based on absolute reflectance (single-channel model) or a ratio of spectral reflectances in two bands (dual-channel model). These models are calibrated by usingWV-2multispectral imagery acquired early in the melt season and depth measurements from a high resolutionWV-2 DEM over the same lake basins when devoid of water. The calibrated models are then validated with different lakes in the area, for which we determined depths. Lake depth estimates based on measurements recorded in WV-2's blue (450-510 nm), green (510-580 nm), and red (630-690 nm) bands and dual-channel modes (blue/green, blue/red, and green/red band combinations) had near-zero bias, an average root-mean-squared deviation of 0.4 m (relative to post-drainage DEMs), and an average volumetric error of b1%. The approach outlined in this study - image-based calibration of depth-retrieval models - significantly improves spaceborne supraglacial bathymetry retrievals, which are completely independent from in situ measurements.

Spectrally-based depth-retrieval models↗
DOE OSTI2016

Evaluation of mineral reactive surface area estimates for prediction of reactivity of a multi-mineral sediment

Our limited understanding of mineral reactive surface area contributes to significant uncertainties in quantitative simulations of reactive chemical transport in subsurface processes. Continuum formulations for reactive transport typically use a number of different approximations for reactive surface area, including geometric, specific, and effective surface area. In this work, reactive surface area estimates are developed and evaluated for their ability to predict dissolution rates in a well-stirred flow-through reactor experiment using disaggregated samples from the Nagaoka pilot CO 2 injection site (Japan). The disaggregated samples are reacted with CO 2 acidified synthetic brine under conditions approximating the field conditions and the evolution of solute concentrations in the reactor effluent is tracked over time. The experiments, carried out in fluid-dominated conditions at a pH of 3.2 for 650 h, resulted in substantial dissolution of the sample and release of a disproportionately large fraction of the divalent cations. Traditional reactive surface area estimation methods, including an adjusted geometric surface area and a BET-based surface area, are compared to a newly developed image-based method. Continuum reactive transport modeling is used to determine which of the reactive surface area models provides the best match with the effluent chemistry from the well-stirred reactor. The modeling incorporates laboratory derived mineral dissolution rates reported in the literature and the initial modal mineralogy of the Nagaoka sediment was determined from scanning electron microscopy (SEM) characterization. The closest match with the observed steady-state effluent concentrations was obtained using specific surface area estimates from the image-based approach supplemented by literature-derived BET measurements. To capture the evolving effluent chemistry, particularly over the first 300 h of the experiment, it was also necessary to account for the grain size distribution in the sediment and the presence of a highly reactive volcanic glass phase that shows preferential cation leaching.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2008

Radiometric Modeling and Calibration of the Geostationary Imaging Fourier Transform Spectrometer (GIFTS)Ground Based Measurement Experiment

The ultimate remote sensing benefits of the high resolution Infrared radiance spectrometers will be realized with their geostationary satellite implementation in the form of imaging spectrometers. This will enable dynamic features of the atmosphere s thermodynamic fields and pollutant and greenhouse gas constituents to be observed for revolutionary improvements in weather forecasts and more accurate air quality and climate predictions. As an important step toward realizing this application objective, the Geostationary Imaging Fourier Transform Spectrometer (GIFTS) Engineering Demonstration Unit (EDU) was successfully developed under the NASA New Millennium Program, 2000-2006. The GIFTS-EDU instrument employs three focal plane arrays (FPAs), which gather measurements across the long-wave IR (LWIR), short/mid-wave IR (SMWIR), and visible spectral bands. The GIFTS calibration is achieved using internal blackbody calibration references at ambient (260 K) and hot (286 K) temperatures. In this paper, we introduce a refined calibration technique that utilizes Principle Component (PC) analysis to compensate for instrument distortions and artifacts, therefore, enhancing the absolute calibration accuracy. This method is applied to data collected during the GIFTS Ground Based Measurement (GBM) experiment, together with simultaneous observations by the accurately calibrated AERI (Atmospheric Emitted Radiance Interferometer), both simultaneously zenith viewing the sky through the same external scene mirror at ten-minute intervals throughout a cloudless day at Logan Utah on September 13, 2006. The accurately calibrated GIFTS radiances are produced using the first four PC scores in the GIFTS-AERI regression model. Temperature and moisture profiles retrieved from the PC-calibrated GIFTS radiances are verified against radiosonde measurements collected throughout the GIFTS sky measurement period. Using the GIFTS GBM calibration model, we compute the calibrated radiances from data collected during the moon tracking and viewing experiment events. From which, we derive the lunar surface temperature and emissivity associated with the moon viewing measurements.

Tian, Jialin↗
DOE OSTI2016

Predicting variation in subject thermal response during transcranial magnetic resonance guided focused ultrasound surgery: Comparison in seventeen subject datasets

Purpose: In transcranial magnetic resonance-guided focused ultrasound (tcMRgFUS) treatments, the acoustic and spatial heterogeneity of the skull cause reflection, absorption, and scattering of the acoustic beams. These effects depend on skull-specific parameters and can lead to patient-specific thermal responses to the same transducer power. In this work, the authors develop a simulation tool to help predict these different experimental responses using 3D heterogeneous tissue models based on the subject CT images. The authors then validate and compare the predicted skull efficiencies to an experimental metric based on the subject thermal responses during tcMRgFUS treatments in a dataset of seventeen human subjects. Methods: Seventeen human head CT scans were used to create tissue acoustic models, simulating the effects of reflection, absorption, and scattering of the acoustic beam as it propagates through a heterogeneous skull. The hybrid angular spectrum technique was used to model the acoustic beam propagation of the InSightec ExAblate 4000 head transducer for each subject, yielding maps of the specific absorption rate (SAR). The simulation assumed the transducer was geometrically focused to the thalamus of each subject, and the focal SAR at the target was used as a measure of the simulated skull efficiency. Experimental skull efficiency for each subject was calculated using the thermal temperature maps from the tcMRgFUS treatments. Axial temperature images (with no artifacts) were reconstructed with a single baseline, corrected using a referenceless algorithm. The experimental skull efficiency was calculated by dividing the reconstructed temperature rise 8.8 s after sonication by the applied acoustic power. Results: The simulated skull efficiency using individual-specific heterogeneous models predicts well (R{sup 2} = 0.84) the experimental energy efficiency. Conclusions: This paper presents a simulation model to predict the variation in thermal responses measured in clinical ctMRGFYS treatments while being computationally feasible.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2017

Image-optimized Coronal Magnetic Field Models

We have reported previously on a new method we are developing for using image-based information to improve global coronal magnetic field models. In that work, we presented early tests of the method, which proved its capability to improve global models based on flawed synoptic magnetograms, given excellent constraints on the field in the model volume. In this follow-up paper, we present the results of similar tests given field constraints of a nature that could realistically be obtained from quality white-light coronagraph images of the lower corona. We pay particular attention to difficulties associated with the line-of-sight projection of features outside of the assumed coronagraph image plane and the effect on the outcome of the optimization of errors in the localization of constraints. We find that substantial improvement in the model field can be achieved with these types of constraints, even when magnetic features in the images are located outside of the image plane.

79 ASTRONOMY AND ASTROPHYSICS↗