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All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

SU-F-T-138: Commissioning and Evaluating Dose Computation Models for a Dedicated Proton Line Scanning Beam Nozzle in Eclipse Treatment Planning System

Purpose: In this study, we present an effective method to derive low dose envelope of the proton in-air spot fluence at beam positions other than the isocenter to reduce amount of measurements required for planning commission. Also, we demonstrate commissioning and validation results of this method to the Eclipse treatment planning system (version 13.0.29) for a Sumitomo dedicated proton line scanning beam nozzle. Methods: The in-air spot profiles at five beam-axis positions (±200, ±100 and 0 mm) were obtained in trigger mode using a MP3 Water tank (PTW-Freiburg) and a pinpoint ionization chamber (model 31014, PTW-Freiburg). Low dose envelope (below 1% of the center dose) of the spot profile at isocenter was obtained by repeated point measurements to minimize dosimetry uncertainty. The double Gaussian (DG) model was used to fit and obtain optimal σ1, σ2 and their corresponding weightings through our in-house MATLAB (Mathworks) program. σ1, σ2 were assumed to expand linearly along the beam axis from a virtual source position calculated by back projecting fitted sigmas from the single Gaussian (SG) model. Absolute doses in water were validated using an Advanced Markus chamber at the depth of 2cm with Pristine Peak (BP) R90d ranging from 5–32 cm for 10×10 cm2 scanned fields. The field size factors were verified with square fields from 2 to 20 cm at 2cm and before BP depth. Results: The absolute dose outputs were found to be within ±3%. For field size factor, the agreement between calculated and measurement were within ±2% at 2cm and ±3% before BP, except for the field size below 2×2 cm2. Conclusion: The double Gaussian model was found to be sufficient for characterizing the Sumitomo dedicated proton line scanning nozzle. With our effective double Gaussian fitting method, we are able to save significant proton beam time with acceptable output accuracy.

60 APPLIED LIFE SCIENCES↗
NASA NTRS2004

Neural network uncertainty assessment using Bayesian statistics: a remote sensing application

Neural network (NN) techniques have proved successful for many regression problems, in particular for remote sensing; however, uncertainty estimates are rarely provided. In this article, a Bayesian technique to evaluate uncertainties of the NN parameters (i.e., synaptic weights) is first presented. In contrast to more traditional approaches based on point estimation of the NN weights, we assess uncertainties on such estimates to monitor the robustness of the NN model. These theoretical developments are illustrated by applying them to the problem of retrieving surface skin temperature, microwave surface emissivities, and integrated water vapor content from a combined analysis of satellite microwave and infrared observations over land. The weight uncertainty estimates are then used to compute analytically the uncertainties in the network outputs (i.e., error bars and correlation structure of these errors). Such quantities are very important for evaluating any application of an NN model. The uncertainties on the NN Jacobians are then considered in the third part of this article. Used for regression fitting, NN models can be used effectively to represent highly nonlinear, multivariate functions. In this situation, most emphasis is put on estimating the output errors, but almost no attention has been given to errors associated with the internal structure of the regression model. The complex structure of dependency inside the NN is the essence of the model, and assessing its quality, coherency, and physical character makes all the difference between a blackbox model with small output errors and a reliable, robust, and physically coherent model. Such dependency structures are described to the first order by the NN Jacobians: they indicate the sensitivity of one output with respect to the inputs of the model for given input data. We use a Monte Carlo integration procedure to estimate the robustness of the NN Jacobians. A regularization strategy based on principal component analysis is proposed to suppress the multicollinearities in order to make these Jacobians robust and physically meaningful.

Neural Networks (Computer)↗
DOE OSTI2013

Fully Differential Monte-Carlo Generator Dedicated to TMDs and Bessel-Weighted Asymmetries

We present studies of double longitudinal spin asymmetries in semi-inclusive deep inelastic scattering using a new dedicated Monte Carlo generator, which includes quark intrinsic transverse momentum within the generalized parton model based on the fully differential cross section for the process. Additionally, we apply Bessel-weighting to the simulated events to extract transverse momentum dependent parton distribution functions and also discuss possible uncertainties due to kinematic correlation effects.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2011

Task-based weights for photon counting spectral x-ray imaging

Purpose: To develop a framework for taking the spatial frequency composition of an imaging task into account when determining optimal bin weight factors for photon counting energy sensitive x-ray systems. A second purpose of the investigation is to evaluate the possible improvement compared to using pixel based weights. Methods: The Fourier based approach of imaging performance and detectability index d' is applied to pulse height discriminating photon counting systems. The dependency of d' on the bin weight factors is made explicit, taking into account both differences in signal and noise transfer characteristics across bins and the spatial frequency dependency of interbin correlations from reabsorbed scatter. Using a simplified model of a specific silicon detector, d' values for a high and a low frequency imaging task are determined for optimal weights and compared to pixel based weights. Results: The method successfully identifies bins where a large point spread function degrades detection of high spatial frequency targets. The method is also successful in determining how to downweigh highly correlated bins. Quantitative predictions for the simplified silicon detector model indicate that improvements in the detectability index when applying task-based weights instead of pixel based weights are small for high frequency targets, but could be in excess of 10% for low frequency tasks where scatter-induced correlation otherwise degrade detectability. Conclusions: The proposed method makes the spatial frequency dependency of complex correlation structures between bins and their effect on the system detective quantum efficiency easier to analyze and allows optimizing bin weights for given imaging tasks. A potential increase in detectability of double digit percents in silicon detector systems operated at typical CT energies (100 kVp) merits further evaluation on a real system. The method is noted to be of higher relevance for silicon detectors than for cadmium (zink) telluride detectors.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2016

The mass-sheet degeneracy and time-delay cosmography: analysis of the strong lens RXJ1131-1231

We present extended modelling of the strong lens system RXJ1131-1231 with archival data in two HST bands in combination with existing line-of-sight contribution and velocity dispersion estimates. Our focus is on source size and its influence on time-delay cosmography. We therefore examine the impact of mass-sheet degeneracy and especially the degeneracy pointed out by Schneider and Sluse (2013) [1] using the source reconstruction scale. We also extend on previous work by further exploring the effects of priors on the kinematics of the lens and the external convergence in the environment of the lensing system. Our results coming from RXJ1131-1231 are given in a simple analytic form so that they can be easily combined with constraints coming from other cosmological probes. We find that the choice of priors on lens model parameters and source size are subdominant for the statistical errors for H {sub 0} measurements of this systems. The choice of prior for the source is sub-dominant at present (2% uncertainty on H {sub 0}) but may be relevant for future studies. More importantly, we find that the priors on the kinematic anisotropy of the lens galaxy have a significant impact on our cosmological inference. When incorporating all the above modeling uncertainties, we find H {sub 0} = 86.6{sup +6.8}{sub -6.9} km s{sup -1} Mpc{sup -1}, when using kinematic priors similar to other studies. When we use a different kinematic prior motivated by Barnabè et al. (2012) [2] but covering the same anisotropic range, we find H {sub 0} = 74.5{sup +8.0}{sub -7.8} km s{sup -1} Mpc{sup -1}. This means that the choice of kinematic modeling and priors have a significant impact on cosmographic inferences. The way forward is either to get better velocity dispersion measures which would down weight the impact of the priors or to construct physically motivated priors for the velocity dispersion model.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1989

Age structure of refractory interstellar dust and isotopic consequences

A sputtering and recycling Monte Carlo model, developed by Liffman and Clayton (1988) is used to calculate the distribution of existence times of the matter in interstellar dust composed of refractory metals. The mean age of each dust particle is defined not as the time it has existed but rather as the mass-weighted existence times of its parts at t = 6 Gyr of the modeled solar system formation. It is shown that Galactic evolution generates a mean correlation, applying to large numbers of particles binned according to size rather than according to individual particles, whose mean ages fluctuate statistically. The cosmochemical consequence is that if interstellar particles can be dynamically sorted into separate size populations during the aggregation history of solar system bodies, the collections of larger grains will constitute matter that is chemically older than collections of smaller grains. The macroscopic age difference generates isotopic anomalies by virtue of the time dependence of the secondary/primary nucleosynthesis yields. Results are compared with three different prescriptions for the sputtering of interstellar dust.

Clayton, Donald D.↗
DOE OSTI2020

The Influence of Aqueous Dispersivity on Transport of Radiological Material at LANL MDA G - 20450

Aqueous dispersivity is a phenomenon by which a solute moving in groundwater mixes with water that does not contain the solute and becomes diluted. Solutes take paths of varying lengths through pore networks or experience slower velocities due to interactions with pore walls. Aqueous dispersivity leads to breakthrough curves with earlier arrival than expected in purely advective systems and persistent 'tails,' or late-arriving, dilute concentrations of the solute. Dispersivity can be longitudinal (in the direction of flow) or transverse (orthogonal to flow). LANL has disposed of radioactive material at Material Disposal Area (MDA) G since the late 1950's. Most of the disposed materials at MDA G are low-level waste (LLW), but other types of radioactive wastes are disposed or stored at the site. For example, there is a collection of remote-handled transuranic waste (RH-TRU) waste in 33 shafts, which were intended to be stored retrievably. Aqueous-phase radionuclides included in models of contaminant transport at MDA G are subject to dispersive processes in porous media of the vadose zone and saturated zone. To model dispersivity at MDA G probabilistically, we created site-specific distributions of aqueous dispersivity. First, we performed a comprehensive review of peer-reviewed publications, reports from other performance assessments of MDA G, and documentation from sites that were considered similar based on expert opinion, such as Yucca Mountain. Data were included from a wide range of sources, so that distributions developed based on the data reflect the current state of knowledge in properties of the subsurface environment. Data were grouped based on value type (e.g., determined via experiment or used in a different model), rock type, zone type (saturated or unsaturated), and site, and were weighted in the distributions according to their relevance to the site and zone type. We combined Monte Carlo simulation and bootstrapping techniques to produce approximate distributions of mean aqueous dispersivity. Distributions of dispersivity for saturated and unsaturated zone transport are differentiated by data weight and the length scales over which transport occurs. We find that underestimating or disregarding transverse dispersivity may lead to overstating simulated well capture in the saturated zone at MDA G. Neglecting transverse dispersivity is a common assumption due in part to use of one-dimensional transport models that do not consider solute spreading orthogonal to flow. Also, we find that variability in longitudinal dispersivity is associated with substantial travel time alterations in the MDA G unsaturated zone and in simulated contaminant breakthrough times at a downstream observation plane in the MDA G saturated zone. Finally, at large scales (>1000 m), a linear trend between the dispersivity coefficient and length over which transport occurs may overestimate the dispersivity coefficient. Future modeling work with application to solute spreading could include interacting advective and diffusive zones in the highly fractured basalt below MDA G. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2019

Effect of Short-Range Correlations on Spectral Properties of Doped Mott Insulators

In the framework of the cluster perturbation theory for the 2D Hubbard and Hubbard-Holstein models at low hole doping, we have studied the effect of local and short-range correlations in strongly correlated systems on the anomalous features in the electronic spectrum by investigating the fine structure of quasiparticle bands. Different anomalous features of spectrum are obtained as the result of intrinsic properties of strongly correlated electron and polaron bands in the presence of short-range correlations. Particularly, features similar to the electron-like Fermi-pockets of cuprates at hole doping p ∼ 0.1 are obtained without ad hoc introducing a charge density wave order parameter within the Hubbard model in a unified manner with other known peculiarities of the pseudogap phase like Fermi-arcs, pockets, waterfalls, and kink-like features. The Fermi surface is mainly formed by dispersive quasiparticle bands with large spectral weight, formed by coherent low-energy exications. Within the Hubbard-Holstein model at moderate phonon frequencies, we show that modest values of local electron-phonon interaction are capable of introducing low-energy kink-like features and affecting the Fermi surface by hybridization of the fermionic quasiparticle bands with the Franck-Condon resonances.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
NASA NTRS2003

Finite-Rate Ablation Boundary Conditions for Carbon-Phenolic Heat-Shield

A formulation of finite-rate ablation surface boundary conditions, including oxidation, nitridation, and sublimation of carbonaceous material with pyrolysis gas injection, has been developed based on surface species mass conservation. These surface boundary conditions are discretized and integrated with a Navier-Stokes solver. This numerical procedure can predict aerothermal heating, chemical species concentration, and carbonaceous material ablation rate over the heatshield surface of re-entry space vehicles. In this study, the gas-gas and gas-surface interactions are established for air flow over a carbon-phenolic heatshield. Two finite-rate gas-surface interaction models are considered in the present study. The first model is based on the work of Park, and the second model includes the kinetics suggested by Zhluktov and Abe. Nineteen gas phase chemical reactions and four gas-surface interactions are considered in the present model. There is a total of fourteen gas phase chemical species, including five species for air and nine species for ablation products. Three test cases are studied in this paper. The first case is a graphite test model in the arc-jet stream; the second is a light weight Phenolic Impregnated Carbon Ablator at the Stardust re-entry peak heating conditions, and the third is a fully dense carbon-phenolic heatshield at the peak heating point of a proposed Mars Sample Return Earth Entry Vehicle. Predictions based on both finite-rate gas- surface interaction models are compared with those obtained using B' tables, which were created based on the chemical equilibrium assumption. Stagnation point convective heat fluxes predicted using Park's finite-rate model are far below those obtained from chemical equilibrium B' tables and Zhluktov's model. Recession predictions from Zhluktov's model are generally lower than those obtained from Park's model and chemical equilibrium B' tables. The effect of species mass diffusion on predicted ablation rate is also examined.

Chen, Y.-K.↗
NASA NTRS1981

Thermodynamics and kinetics of the sulfation of porous calcium silicate

The sulfation of plasma sprayed calcium silicate in flowing SO2/air mixtures at 900 and 1000 C was investigated thermogravimetrically. Reaction products were analyzed using electron microprobe and X-ray diffraction analysis techniques, and results were compared with thermodynamic predictions. The percentage, by volume, of SO2 in air was varied between 0.036 and 10 percent. At 10 percent SO2 the weight gain curve displays a concave downward shoulder early in the sulfation process. An analytical model was developed which treats the initial process as one which decays exponentially with increasing time and the subsequent process as one which decays exponentially with increasing weight gain. At lower SO2 levels the initial rate is controlled by the reactant flow rate. At 1100 C and 0.036 percent SO2 there is no reaction, in agreement with thermodynamic predictions.

Miller, R. A.↗
NASA NTRS1987

Magnetic suspension and balance system (MSBS) advanced study.I - System design

A magnetic suspension and balance system is designed to support models of aircraft or other objects in wind tunnels by means of magnetic forces. Major design improvements have been achieved, resulting in reductions of the system size, weight, and cost. These improvements are due to: (1) the use of holmium in the model core to increase its magnetic moment, (2) the use of a powerful new permanent magnet material in the model wings, (3) a new arrangement for the roll coils, and (4) the use of a nonmetallic structure to eliminate eddy current losses. The conceptual design of the holmium core superconductive solenoid and of the new permanent magnet wing assembly is described in detail. The discussion includes comparisons of the pole strengths for different model core magnets, the design of a superconducting solenoid and cryostat, and the analysis of model wing magnetic requirements.

Boom, Roger W.↗
DOE OSTI2012

Effects and detectability of quasi-single field inflation in the large-scale structure and cosmic microwave background

Quasi-single field inflation predicts a peculiar momentum dependence in the squeezed limit of the primordial bispectrum which smoothly interpolates between the local and equilateral models. This dependence is directly related to the mass of the isocurvatons in the theory which is determined by the supersymmetry. Therefore, in the event of detection of a non-zero primordial bispectrum, additional constraints on the parameter controlling the momentum-dependence in the squeezed limit becomes an important question. We explore the effects of these non-Gaussian initial conditions on large-scale structure and the cosmic microwave background, with particular attention to the galaxy power spectrum at large scales and scale-dependence corrections to galaxy bias. We determine the simultaneous constraints on the two parameters describing the QSF bispectrum that we can expect from upcoming large-scale structure and cosmic microwave background observations. We find that for relatively large values of the non-Gaussian amplitude parameters, but still well within current uncertainties, galaxy power spectrum measurements will be able to distinguish the QSF scenario from the predictions of the local model. A CMB likelihood analysis, as well as Fisher matrix analysis, shows that there is also a range of parameter values for which Planck data may be able distinguish between QSF models and the related local and equilateral shapes. Given the different observational weightings of the CMB and LSS results, degeneracies can be significantly reduced in a joint analysis.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2014

Improved Wind Turbine Drivetrain Reliability using a Combined Experimental, Computational, and Analytical Approach (Presentation)

Nontorque loads induced by the wind turbine rotor overhang weight and aerodynamic forces can greatly affect drivetrain loads and responses. If not addressed properly, these loads can result in a decrease in gearbox component life. This work uses analytical modeling, computational modeling, and experimental data to evaluate a unique drivetrain design that minimize the effects of nontorque loads on gearbox reliability: the Pure Torque drivetrain developed by Alstom. The drivetrain has a hub-support configuration that transmits nontorque loads directly into the tower rather than through the gearbox as in other design approaches. An analytical model of Alstom's Pure Torque drivetrain provides insight into the relationships among turbine component weights, aerodynamic forces, and the resulting drivetrain loads. Main shaft bending loads are orders of magnitude lower than the rated torque and are hardly affected by wind speed and turbine operations.

17 WIND ENERGY↗
DOE OSTI2025

Fusion burn-propagation simulations using the collisional and radiative particle-in-cell code TRIFORCE

The ability to accurately model burn propagation in inertial confinement fusion plasmas is crucial for advancing fusion energy research. This work presents enhancements to the triforce hybrid fluid-kinetic multiphysics code, focusing on its kinetic half, which employs the particle-in-cell (PIC) method with Monte Carlo collisions (MCC). We use a moment-preserving collision model that mitigates numerical noise, particularly in spherical geometries where particle weights vary significantly. Additionally, we refine the treatment of inverse bremsstrahlung to account for electron–ion collision frequency reductions in degenerate plasmas and incorporate a blackbody radiation source to enable realistic photon injection. These improvements enable the simulation of 1-dimensional (1D) spherical fusion burn propagation in deuterium–tritium plasmas. Benchmark comparisons with the hydra radiation-hydrodynamics code confirm that triforce accurately captures the dynamics of hot-spot expansion and burn propagation, demonstrating sensitivity to ignition thresholds consistent with theoretical models. Findings show the ignition cliff to be less steep in our work compared to radiation-hydrodynamic modeling. These results highlight the role of kinetic effects in fusion ignition physics and underscore the necessity of hybrid fluid-kinetic models for advancing predictive capabilities in high-energy-density plasma systems.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS1974

Digital adaptive flight control design using single stage model following indices

Simple mechanical linkages are often unable to cope with many control problems associated with high-performance aircraft. This has led to the development of digital fly-by-wire control systems and in particular digital adaptive controllers that can be efficiently adjusted during system operation. To this effect, a control law has been derived based upon the minimization of a single-stage weighted combination of control energy and the squared error between the states of a linear plant and model. This control logic is interfaced with an on-line weighted least-squares estimator and a Kalman state filter. The utility of the resultant control system is illustrated by its application to the linearized dynamics of a typical fighter aircraft.

Alag, G.↗
DOE OSTI2019

Uniformity Is Key in Defining Structure–Function Relationships for Atomically Dispersed Metal Catalysts: The Case of Pt/CeO 2

Catalysts consisting of atomically dispersed Pt (Pt iso ) species on CeO 2 supports have received recent interest due to their potential for efficient metal utilization in catalytic convertors. However, discrepancies exist between the behavior (reducibility, interaction strength with adsorbates) of high surface area Pt iso /CeO 2 systems and of well-defined surface science and computational model systems, suggesting differences in Pt local coordination in the two classes of materials. Here, we reconcile these differences by demonstrating that high surface area Pt iso /CeO 2 synthesized at low Pt loadings (<0.1% weight) exhibit resistance to reduction and sintering up to 500 °C in 0.05 bar H 2 and minimal interactions with CO—properties previously seen only for model system studies. Alternatively, Pt loadings >0.1 weight % produce a distribution of sub-nanometer Pt structures, which are difficult to distinguish using common characterization techniques, and exhibit strong interactions with CO and weak resistance to sintering, even in 0.05 bar H 2 at 50 °C—properties previously seen for high surface area materials. This work demonstrates that low metal loadings can be used to selectively populate the most thermodynamically stable adsorption sites on high surface area supports with atomically dispersed metals. Further, the site uniformity afforded by this synthetic approach is critical for the development of relationships between atomic scale local coordination and functional properties. Comparisons to recent studies of Pt iso /TiO 2 suggest a general compromise between the stability of atomically dispersed metal catalysts and their ability to interact with and activate molecular species.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Fine-tuning TrailMap: The utility of transfer learning to improve the performance of deep learning in axon segmentation of light-sheet microscopy images

Light-sheet microscopy has made possible the 3D imaging of both fixed and live biological tissue, with samples as large as the entire mouse brain. However, segmentation and quantification of that data remains a time-consuming manual undertaking. Machine learning methods promise the possibility of automating this process. This study seeks to advance the performance of prior models through optimizing transfer learning. We fine-tuned the existing TrailMap model using expert-labeled data from noradrenergic axonal structures in the mouse brain. By changing the cross-entropy weights and using augmentation, we demonstrate a generally improved adjusted F1-score over using the originally trained TrailMap model within our test datasets.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

INN Airfoil Tools

This software package contains code to perform airfoil inverse shape design using a sparsified invertible neural network model. This is a specialized deep learning architecture that enables both network weights to be shared to evaluate forward or inverse passes through the network. As a design tool, this network allows practitioners to specify desired aerodynamic and structural properties and generate shapes that satisfy those properties. The invertible neural network is accompanied with tuned parameters as well as software tools to train new models as needed.

Glaws, Andrew↗