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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 523 records · Page 29
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

SU-E-J-201: Investigation of MRI Guided Proton Therapy

Purpose: Image-guided radiation therapy has been employed for cancer treatment to improve the tumor localization accuracy. Radiation therapy with proton beams requires more on this accuracy because the proton beam has larger uncertainty and dramatic dose variation along the beam direction. Among all the image modalities, magnetic-resonance image (MRI) is the best for soft tissue delineation and real time motion monitoring. In this work, we investigated the behavior of the proton beam in magnetic field with Monte Carlo simulations. Methods: A proton Monte Carlo platform, TOPAS, was used for this investigation. Dose calculations were performed with this platform in a 30cmx30cmx30cm water phantom for both pencil and broad proton beams with different energies (120, 150 and 180MeV) in different magnetic fields (0.5T, 1T and 3T). The isodose distributions, dose profiles in lateral and beam direction were evaluated. The shifts of the Bragg peak in different magnetic fields for different proton energies were compared and the magnetic field effects on the characters of the dose distribution were analyzed. Results: Significant effects of magnetic field have been observed on the proton beam dose distributions, especially for magnetic field of 1T and up. The effects are more significant for higher energy proton beam because higher energy protons travel longer distance in the magnetic field. The Bragg peak shift in the lateral direction is about 38mm for 180MeV and 11mm for 120MeV proton beams in 3T magnetic field. The peak positions are retracted back for 6mm and 2mm, respectively. The effect on the beam penumbra and dose falloff at the distal edge of the Bragg peak is negligible. Conclusion: Though significant magnetic effects on dose distribution have been observed for proton beams, MRI guided proton therapy is feasible because the magnetic effects on dose is predictable and can be considered in patient dose calculation.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

Energetic Light Fragment Production Capability in MCNP6

Monte Carlo Methods, Codes, and Applications group within the Computational Physics Division at Los Alamos National Laboratory has led the development of the transport code MCNP6 (Monte Carlo N-Particle transport code, version 6). MCNP6 is a general-purpose, continuous energy, generalized-geometry, time-dependent, Monte-Carlo radiation-transport code designed to track many particle types over broad ranges of energies. It is used around the world in applications ranging from radiation protection and dosimetry, nuclear-reactor design, nuclear criticality safety, detector design and analysis, decontamination and decommissioning, accelerator applications, medical physics, space research, and beyond. At lower energies, the code uses tables of evaluated nuclear data, while for higher energies (> 150 MeV), MCNP6 uses the cascade-exciton model, version 03.03 (CEM03.03), and the Los Alamos quark-gluon string model, version 03.03 (LAQGSM03.03) to model nuclear reactions. Emission of energetic heavy clusters heavier than {sup 4}He from nuclear reactions play a critical role in several applications, including electronics performance in space, human radiation dosages in space or other extreme radiation environments, proton- and hadron-therapy in medical physics, accelerator and shielding applications, and more. None of the available models are able to accurately predict emission of light fragments (LF) from arbitrary reactions. The CEM and LAQGSM event generators in MCNP6 describe quite well the spectra of fragments with sizes up to {sup 4}He across a broad range of target masses and incident energies (up to ∼ 5 GeV for CEM and up to ∼ 1 TeV/A for LAQGSM). However, they do not predict the high-energy tails of LF spectra heavier than {sup 4}He well. Most LF with energies above several tens of MeV are emitted during the precompound stage of a reaction. The 03.03 versions of CEM and LAQGSM do not account for precompound emission of LF larger than {sup 4}He. The goal of this research is to enable MCNP6 to produce high-energy light fragments. These energetic LF may be emitted by our models through three processes: Fermi breakup, preequilibrium, and coalescence. We explore the emission of light fragments through each of these mechanisms and demonstrate an improved agreement with experimental data achieved by extending precompound models to include emission of fragments heavier than {sup 4}He. (authors)

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2016

Meaningful timescales from Monte Carlo simulations of particle systems with hard-core interactions

A new Markov Chain Monte Carlo method for simulating the dynamics of particle systems characterized by hard-core interactions is introduced. In contrast to traditional Kinetic Monte Carlo approaches, where the state of the system is associated with minima in the energy landscape, in the proposed method, the state of the system is associated with the set of paths traveled by the atoms and the transition probabilities for an atom to be displaced are proportional to the corresponding velocities. In this way, the number of possible state-to-state transitions is reduced to a discrete set, and a direct link between the Monte Carlo time step and true physical time is naturally established. The resulting rejection-free algorithm is validated against event-driven molecular dynamics: the equilibrium and non-equilibrium dynamics of hard disks converge to the exact results with decreasing displacement size.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRSDate not supplied

Strategies for Automation of Model Tuning in Multifidelity Trajectory Uncertainty Propagation

Multi-model Monte Carlo methods are efficient strategies to perform forward uncertainty quantification studies in entry, descent, and landing (EDL) applications. These multi-model methods are based on the classical Monte Carlo estimator, but fuse predictions from several low-fidelity models to obtain estimators with greater precision given a prescribed computational budget. The effectiveness of these approaches relies on the magnitudes of correlations between the low-fidelity models and the high-fidelity model, as well as the relative computational costs of all models. Identifying and exploiting the best trade-off between correlation and cost, which ultimately depends on the selection of hyperparameters in the low-fidelity models, is a task often performed by hand or simply inspired by the deterministic understanding available for a specific application. This work extends a preliminary effort,

Marten Thompson↗
NASA NTRS1971

Shock wave structure using nonlinear model Boltzmann equations

The structure of a strong plane shock wave in a monatomic rarefied perfect gas is one of the simplest problems able to be posed in kinetic theory, and one of the hardest to solve. Its simplicity lies in the absence of solid boundaries, geometrical complications, or internal molecular energy. Its difficulty arises from the great departure of the gas from equilibrium within the shock, which invalidates many of the techniques used successfully elsewhere in kinetic theory. In addition to this theoretical challenge, the modern development of ballistics and hypersonic flight has helped to stimulate extensive theoretical and experimental interest in the shock problem. The experimenters in turn have encountered great difficulties on account of the very small physical dimensions of shocks. In fact, until very recently indeed, any close comparisons of theoretical and experimental shock structure results have been rather unprofitable due to the inadequacies of both theory and experiment. During the last few years this situation has been appreciably improved by development of the Monte Carlo method. This allows idealized 'experiments' to be performed on large computers instead of in wind tunnels, using a known intermolecular force law. The most developed of these methods has been shown to be equivalent theoretically to the Boltzmann equation and to give results which agree extremely closely with measurements of high accuracy. Thus Monte Carlo results not only form the soundest basis for our present theoretical knowledge of shock wave structure, but, for purposes of developing other theories, can also be considered a very valuable experimental resource. However, such results remain very expensive to obtain. In this thesis we develop more economical kinetic theory methods for the approximate prediction of shock structure, and compare our results with those of the Monte Carlo method.

Segal, Ben Maurice↗
DOE OSTI2015

Finite element approximation of the radiative transport equation in a medium with piece-wise constant refractive index

The radiative transport equation can be used as a light transport model in a medium with scattering particles, such as biological tissues. In the radiative transport equation, the refractive index is assumed to be constant within the medium. However, in biomedical media, changes in the refractive index can occur between different tissue types. In this work, light propagation in a medium with piece-wise constant refractive index is considered. Light propagation in each sub-domain with a constant refractive index is modeled using the radiative transport equation and the equations are coupled using boundary conditions describing Fresnel reflection and refraction phenomena on the interfaces between the sub-domains. The resulting coupled system of radiative transport equations is numerically solved using a finite element method. The approach is tested with simulations. The results show that this coupled system describes light propagation accurately through comparison with the Monte Carlo method. It is also shown that neglecting the internal changes of the refractive index can lead to erroneous boundary measurements of scattered light.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2017

A dynamical polynomial chaos approach for long-time evolution of SPDEs

We propose a Dynamical generalized Polynomial Chaos (DgPC) method to solve time-dependent stochastic partial differential equations (SPDEs) with white noise forcing. The long-time simulation of SPDE solutions by Polynomial Chaos (PC) methods is notoriously difficult as the dimension of the stochastic variables increases linearly with time. Exploiting the Markovian property of white noise, DgPC implements a restart procedure that allows us to expand solutions at future times in terms of orthogonal polynomials of the measure describing the solution at a given time and the future white noise. The dimension of the representation is kept minimal by application of a Karhunen–Loeve (KL) expansion. Using frequent restarts and low degree polynomials on sparse multi-index sets, the method allows us to perform long time simulations, including the calculation of invariant measures for systems which possess one. We apply the method to the numerical simulation of stochastic Burgers and Navier–Stokes equations with white noise forcing. Our method also allows us to incorporate time-independent random coefficients such as a random viscosity. We propose several numerical simulations and show that the algorithm compares favorably with standard Monte Carlo methods.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2016

Technical Note: Dose gradients and prescription isodose in orthovoltage stereotactic radiosurgery

Purpose: The purpose of this work is to examine the trade-off between prescription isodose and dose gradients in orthovoltage stereotactic radiosurgery. Methods: Point energy deposition kernels (EDKs) describing photon and electron transport were calculated using Monte Carlo methods. EDKs were generated from 10 to 250 keV, in 10 keV increments. The EDKs were converted to pencil beam kernels and used to calculate dose profiles through isocenter from a 4π isotropic delivery from all angles of circularly collimated beams. Monoenergetic beams and an orthovoltage polyenergetic spectrum were analyzed. The dose gradient index (DGI) is the ratio of the 50% prescription isodose volume to the 100% prescription isodose volume and represents a metric by which dose gradients in stereotactic radiosurgery (SRS) may be evaluated. Results: Using the 4π dose profiles calculated using pencil beam kernels, the relationship between DGI and prescription isodose was examined for circular cones ranging from 4 to 18 mm in diameter and monoenergetic photon beams with energies ranging from 20 to 250 keV. Values were found to exist for prescription isodose that optimize DGI. Conclusions: The relationship between DGI and prescription isodose was found to be dependent on both field size and energy. Examining this trade-off is an important consideration for designing optimal SRS systems.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

Bowtie filters for dedicated breast CT: Theory and computational implementation

Purpose: To design bowtie filters with improved properties for dedicated breast CT to improve image quality and reduce dose to the patient. Methods: The authors present three different bowtie filters designed for a cylindrical 14-cm diameter phantom with a uniform composition of 40/60 breast tissue, which vary in their design objectives and performance improvements. Bowtie design #1 is based on single material spectral matching and produces nearly uniform spectral shape for radiation incident upon the detector. Bowtie design #2 uses the idea of basis material decomposition to produce the same spectral shape and intensity at the detector, using two different materials. Bowtie design #3 eliminates the beam hardening effect in the reconstructed image by adjusting the bowtie filter thickness so that the effective attenuation coefficient for every ray is the same. All three designs are obtained using analytical computational methods and linear attenuation coefficients. Thus, the designs do not take into account the effects of scatter. The authors considered this to be a reasonable approach to the filter design problem since the use of Monte Carlo methods would have been computationally intensive. The filter profiles for a cone-angle of 0° were used for the entire length of each filter because the differences between those profiles and the correct cone-beam profiles for the cone angles in our system are very small, and the constant profiles allowed construction of the filters with the facilities available to us. For evaluation of the filters, we used Monte Carlo simulation techniques and the full cone-beam geometry. Images were generated with and without each bowtie filter to analyze the effect on dose distribution, noise uniformity, and contrast-to-noise ratio (CNR) homogeneity. Line profiles through the reconstructed images generated from the simulated projection images were also used as validation for the filter designs. Results: Examples of the three designs are presented. Initial verification of performance of the designs was done using analytical computations of HVL, intensity, and effective attenuation coefficient behind the phantom as a function of fan-angle with a cone-angle of 0°. The performance of the designs depends only weakly on incident spectrum and tissue composition. For all designs, the dynamic range requirement on the detector was reduced compared to the no-bowtie-filter case. Further verification of the filter designs was achieved through analysis of reconstructed images from simulations. Simulation data also showed that the use of our bowtie filters can reduce peripheral dose to the breast by 61% and provide uniform noise and CNR distributions. The bowtie filter design concepts validated in this work were then used to create a computational realization of a 3D anthropomorphic bowtie filter capable of achieving a constant effective attenuation coefficient behind the entire field-of-view of an anthropomorphic breast phantom. Conclusions: Three different bowtie filter designs that vary in performance improvements were described and evaluated using computational and simulation techniques. Results indicate that the designs are robust against variations in breast diameter, breast composition, and tube voltage, and that the use of these filters can reduce patient dose and improve image quality compared to the no-bowtie-filter case.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2017

Implicit sampling combined with reduced order modeling for the inversion of vadose zone hydrological data

Bayesian inverse modeling techniques are computationally expensive because many forward simulations are needed when sampling the posterior distribution of the parameters. Here, in this paper, we combine the implicit sampling method and generalized polynomial chaos expansion (gPCE) to significantly reduce the computational cost of performing Bayesian inverse modeling. There are three steps in this approach: (1) find the maximizer of the likelihood function using deterministic approaches; (2) construct a gPCE-based surrogate model using the results from a limited number of forward simulations; and (3) efficiently sample the posterior distribution of the parameters using implicit sampling method. The cost of constructing the gPCE-based surrogate model is further decreased by using sparse Bayesian learning to reduce the number of gPCE coefficients that have to be determined. We demonstrate the approach for a synthetic ponded infiltration experiment simulated with TOUGH2. The surrogate model is highly accurate with mean relative error that is < 0.035% in predicting saturation and < 0.25% in predicting the likelihood function. The posterior distribution of the parameters obtained using our proposed technique is nearly indistinguishable from the results obtained from either an implicit sampling method or a Markov chain Monte Carlo method utilizing the full mode.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

SSA Monte Carlo and Master Equation Modeling of Neutron Leakage Distributions

Strongly stochastic neutron populations in highly subcritical multiplying media containing weak spontaneous fission sources are unique indicators of the presence of SNM. For instance, in neutron multiplicity counting, an extended tail in the count number probability distribution is observed that is a characteristic of and sensitive to the amount of SNM present. Theoretical modeling and efficient computation of stochastic neutron distributions are complementary to experimental measurements and moreover shed light on the fundamental interactions and transport processes that underlie nuclear signatures. Modeling approaches that are intermediate between gross-system level models and high-fidelity but computationally demanding Monte Carlo simulations are of particular interest in this regard. Furthermore we present three advances on existing work in point kinetic or lumped geometry: (i) implementation of the Stochastic Simulation Algorithm (SSA), a system state-updating Monte Carlo method that is more e cient than single-event Monte Carlo in lumped geometries, (ii) application of the backward Master equation to obtain time-gated count moments, and (iii) reconstructing the count number distribution from the deterministically computed moments using a generalized Laguerre polynomial expansion.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS1974

Radiative transfer of visible radiation in turbid atmosphere

Methods are presented for solving radiative transfer problems; they include the doubling method and the closely related matrix method, iterative method, Chandrasekhar's method of discrete ordinates, and Monte Carlo method. To consider radiation transport through turbid atmosphere, an atmospheric model was developed characterizing aerosols by parameters. Intensity and polarization of radiation in turbid atmospheres is discussed, as well as lower atmospheric heating due to solar radiation absorption by aerosols.

Yamamoto, G.↗
DOE OSTI2014

WE-G-BRE-04: Gold Nanoparticle Induced Vasculature Damage for Proton Therapy: Monte Carlo Simulation

Purpose: The aim of this work is to investigate the gold nanoparticle (GNP) induced vasculature damage in a proton beam. We compared the results using a clinical proton beam, 6MV photon beam and two kilovoltage photon beams. Methods: Monte Carlo simulations were carried out using TOPAS (TOol for PArticle Simulation) to obtain the spatial dose distribution in close proximity to GNPs up to 20μm distance. The spatial dose distribution was used as an input to calculate the additional dose deposited to the blood vessels. For this study, GNP induced vasculature damage is evaluated for three particle sources (proton beam, MV photon beam and kV photon beam), various treatment depths for each particle source, various GNP uptakes and three different vessel diameters (8μm, 14μm and 20μm). Results: The result shows that for kV photon, GNPs induce more dose in the vessel wall for 150kVp photon source than 250kVp. For proton therapy, GNPs cause more dose in the vessel wall at shallower treatment depths. For 6MV photons, GNPs induce more dose in the vessel wall at deeper treatment depths. For the same GNP concentration and prescribed dose, the additional dose at the inner vessel wall is 30% more than the prescribed dose for the kVp photon source, 15% more for the proton source and only 2% more for the 6MV photon source. In addition, the dose from GNPs deceases sharper for proton therapy than kVp photon therapy as the distance from the vessel inner wall increases. Conclusion: We show in this study that GNPs can potentially be used to enhance radiation therapy by causing vasculature damage using clinical proton beams. The GNP induced damage for proton therapy is less than for the kVp photon source but significantly larger than for the clinical MV photon source.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2015

Statistics of X-ray flares of Sagittarius A{sup ⋆}: Evidence for solar-like self-organized criticality phenomena

X-ray flares have routinely been observed from the supermassive black hole at our Galactic center, Sagittarius A{sup ⋆} (Sgr A{sup ⋆}). The nature of these flares remains largely unclear, despite many theoretical models. In this paper, we study the statistical properties of the Sgr A{sup ⋆} X-ray flares by fitting the count rate (CR) distribution and the structure function of the light curve with a Markov Chain Monte Carlo method. With the 3-million-second Chandra observations accumulated in the Sgr A{sup ⋆} X-ray Visionary Project, we construct the theoretical light curves through Monte Carlo simulations. We find that the 2–8 keV X-ray light curve can be decomposed into a quiescent component with a constant CR of 6×10{sup −3} count s{sup −1} and a flare component with a power-law fluence distribution dN/dE∝E{sup −α{sub E}} with α{sub E}=1.65±0.17. The duration–fluence correlation can also be modeled as a power law T∝E{sup α{sub E}{sub T}} with α{sub ET}<0.55 (95% confidence). These statistical properties are consistent with the theoretical prediction of the self-organized criticality system with the spatial dimension S = 3. We suggest that the X-ray flares represent plasmoid ejections driven by magnetic reconnection (similar to solar flares) in the accretion flow onto the black hole.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2014

A fixed-node Diffusion Monte Carlo study of the 1,2,3-tridehydrobenzene triradical

The electronic structure of 1,2,3-tridehydrobenzene was investigated using quantum Monte Carlo methods. The radical contains two low-lying electronic states that are nearly degenerate adiabatically (within 2 kcal/mol separation), according to previous coupled cluster calculations. We performed Diffusion Monte Carlo (DMC) calculations starting from Multi-Reference Configuration Interaction (MRCI) trial wavefunctions, with a complete active space (CAS) containing 9 electrons in 9 orbitals, CAS(9,9). Our converged DMC results are in close agreement with the best coupled-cluster results, and further strengthen the assignment of a {sup 2}A{sub 1} ground state.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗