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At least 469 records · Page 26
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Quantum Monte Carlo benchmarking of large noncovalent complexes in the L7 benchmark set

We have used diffusion Monte Carlo (DMC) to perform calculations on the L7 benchmark set. DMC is a stochastic numerical integration scheme in real-space and part of a larger set of quantum Monte Carlo methods. The L7 set was designed to test the ability of electronic structure methods to include dispersive interactions. While the agreement between DMC and quantum-chemical state-of-the-art methods is excellent for some of the structures, there are significant differences in others. In contrast to wavefunction-based quantum chemical methods, DMC is a first-principle many-body method with the many-body wavefunction evolving in real space. It includes explicitly all electron–electron interactions and is relatively insensitive to the size of the basis set.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Uncertainty Quantification of Geophysical Inversion Using Stochastic Partial Differential Equations (LDRD #218329)

This report summarizes work completed under the Laboratory Directed Research and Development (LDRD) project "Uncertainty Quantification of Geophysical Inversion Using Stochastic Differential Equations." Geophysical inversions often require computationally expensive algorithms to find even one solution, let alone propagating uncertainties through to the solution domain. The primary purpose of this project was to find more computationally efficient means to approximate solution uncertainty in geophysical inversions. We found multiple computationally efficient methods of propagating Earth model uncertainty into uncertainties in solutions of full waveform seismic moment tensor inversions. However, the optimum method of approximating the uncertainty in these seismic source solutions was to use the Karhunen-Love theorem with data misfit residuals. This method was orders of magnitude more computationally efficient than traditional Monte Carlo methods and yielded estimates of uncertainty that closely approximated those of Monte Carlo. We will summarize the various methods we evaluated for estimating uncertainty in seismic source inversions as well as work toward this goal in the realm of 3-D seismic tomographic inversion uncertainty.

58 GEOSCIENCES↗
DOE OSTI2014

Hydrogen adsorption in metal-organic frameworks: The role of nuclear quantum effects

The role of nuclear quantum effects on the adsorption of molecular hydrogen in metal-organic frameworks (MOFs) has been investigated on grounds of Grand-Canonical Quantized Liquid Density-Functional Theory (GC-QLDFT) calculations. For this purpose, we have carefully validated classical H{sub 2}-host interaction potentials that are obtained by fitting Born-Oppenheimer ab initio reference data. The hydrogen adsorption has first been assessed classically using Liquid Density-Functional Theory and the Grand-Canonical Monte Carlo methods. The results have been compared against the semi-classical treatment of quantum effects by applying the Feynman-Hibbs correction to the Born-Oppenheimer-derived potentials, and by explicit treatment within the GC-QLDFT. The results are compared with experimental data and indicate pronounced quantum and possibly many-particle effects. After validation calculations have been carried out for IRMOF-1 (MOF-5), GC-QLDFT is applied to study the adsorption of H{sub 2} in a series of MOFs, including IRMOF-4, -6, -8, -9, -10, -12, -14, -16, -18, and MOF-177. Finally, we discuss the evolution of the H{sub 2} quantum fluid with increasing pressure and lowering temperature.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2014

Deterministic Simulation of First-Order Scattering in a Clinical X-ray Computed Tomography Scanner - Paper 81

In nondestructive testing (NDT) and medical diagnostic x-ray imaging (photon energy<140 keV), scattered x-ray caused by Compton and Rayleigh scattering should be eliminated. Scattered x-ray photons reduce image contrast, increase image noise, and introduce artifact into the reconstructed computed tomography (CT) images. In cone-beam CT, where the coverage of the x-ray beam and the area of the detector are significantly larger than those in fan-beam CT, x-ray photon scatter is one of the major sources of image degradation. The artifacts caused by scattered x-ray photon can be divided into two categories: 1) low spatial frequency scatter profile adds a positive bias to the detected radiation signal, thus reducing the effective attenuation of the imaged object, resulting in a negative bias in the measured linear attenuation coefficient in the image; 2) a high spatial frequency scatter profile causes a differential artifact, such as shading in uniform regions. A real x-ray scan is composed of both low and high frequency scatter profiles. Thus, the key to a successful scatter correction is the ability to accurately capture the scatter profile of a real x-ray imaging scan. The most accurate method for estimating a scatter profile is the Monte Carlo simulation. However, the computation cost of the Monte Carlo method makes it unfeasible for simulating real and complex scan geometries in clinical settings. A practical yet accurate scatter profile estimation method is through ray tracing techniques, where the scatter profiles are computed by tracking rays through the object's volume. The x-ray from the source is tracked when it interacts with the material in the volume. The interaction creates scattered x-rays, in all possible directions. These rays are again either attenuated or scattered, creating cascaded scatter events. In x-ray CT, the first-order scattering (where only one scatter interaction is encountered) accounts for the most severe image artifacts since this first-order scatter contains a high frequency component of the scatter profile. Previous studies have shown that ray tracing techniques are quite effective in simulating the contribution of first-order scattering in radiological images. In this study, a similar ray tracing technique is applied to simulate the scatter profile of a real x-ray computed tomography (CT) scan in clinical settings. A good agreement has been found between the simulated scatter profile and the experimental measurement result. (authors)

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2014

Sci—Thur AM: YIS - 06: An EPID-based 3D patient dose verification method for SBRT-VMAT delivery

Purpose: Stereotactic body radiation therapy (SBRT) delivered via volumetric modulated arc therapy (VMAT) can strongly benefit from an in vivo patient dose verification due to the large doses per fraction. Electronic portal imaging devices (EPIDs) can be utilized as a patient dose dosimeter. In this work we present a physics-based model which utilizes on-treatment EPID images to reconstruct the dose delivered to an anthropomorphic phantom during SBRT-VMAT delivery. Methods: An SBRT linac beam was modeled using Monte Carlo methods and verified with measured data. Our dose reconstruction model back-projects EPID measured focal fluence upstream of the patient and adds a predicted extra-focal fluence component. This fluence is forward projected onto the patient's density matrix and convolved with dose kernels to calculate dose. The model was validated for two prostate, three lung, and two spine SBRT-VMAT treatments. Results were compared to the treatment planning system's calculation. Results: 2%/2 mm chi comparison calculations gave pass rates for the whole volume, infield, and high dose region respectively, and no lower than: 98%, 95%, 99% for the prostate plans, 99%, 92%, 85% for the lung plans, and 91%, 85%, 81% for the spine plans. A 3%/3mm calculation gave pass rates no lower than 99%, 94%, and 90% for all dose regions for the prostate, lung, and spine respectively. Conclusions: We have developed a physics-based model which calculates delivered dose to phantom (or patient) for SBRT-VMAT delivery using on treatment EPID images. The accuracy of the results has allowed us to test this model clinically.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

WE-G-BRD-05: Inline Magnetic Fields Enhance Tumor Dose for Small Lung Cancers

Purpose: To report on significant dose enhancement effects caused by magnetic fields aligned parallel to 6MV photon beam radiotherapy of small lung tumors. Findings are applicable to future inline MRI-guided radiotherapy systems. Methods: 9 clinical lung plans were recalculated using Monte Carlo methods and external inline (parallel to the beam direction) magnetic fields of 0.5 T, 1.0 T and 3 T were included. Three plans were 6MV 3D-CRT and six were 6MV IMRT. The GTV’s ranged from 0.8 cc to 73 cc, while the PTV ranged from 1 cc to 180 cc. Results: The inline magnetic field has a moderate impact in lung dose distributions by reducing the lateral scatter of secondary electrons and causing a small local dose increase. Superposition of multiple small beams acts to superimpose the small dose increases and can lead to significant dose enhancements, especially when the GTV is low density. Two plans with very small, low mean density GTV’s (<1 cc, ρ(mean)<0.35g/cc) showed uniform increases of 16% and 23% at 1 T throughout the PTV. Three plans with moderate mean density PTV’s (3–13 cc, ρ(mean)=0.58–0.67 g/cc) showed 6% mean dose enhancement at 1 T in the PTV, however not uniform throughout the GTV/PTV. Replanning would benefit these cases. The remaining 5 plans had large dense GTV’s (∼ 1 g/cc) and so only a minimal (<2%) enhancement was seen. In general the mean dose enhancement at 0.5 T was 60% less than 1 T, while 5–50% higher at 3 T. Conclusions: A paradigm shift in the efficacy of small lung tumor radiotherapy is predicted with future inline MRI-linac systems. This will be achieved by carefully taking advantage of the reduction of lateral electronic disequilibrium withing lung tissue that is induced naturally inside strong inline magnetic fields.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2017

Analytical Assessment for Transient Stability Under Stochastic Continuous Disturbances

Here, with the growing integration of renewable power generation, plug-in electric vehicles, and other sources of uncertainty, increasing stochastic continuous disturbances are brought to power systems. The impact of stochastic continuous disturbances on power system transient stability attracts significant attention. To address this problem, this paper proposes an analytical assessment method for transient stability of multi-machine power systems under stochastic continuous disturbances. In the proposed method, a probability measure of transient stability is presented and analytically solved by stochastic averaging. Compared with the conventional method (Monte Carlo simulation), the proposed method is many orders of magnitude faster, which makes it very attractive in practice when many plans for transient stability must be compared or when transient stability must be analyzed quickly. Also, it is found that the evolution of system energy over time is almost a simple diffusion process by the proposed method, which explains the impact mechanism of stochastic continuous disturbances on transient stability in theory.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Deterministic-Monte Carlo Hybrid Methods for Eigenvalue Sensitivity Coefficient Calculations [Slides]

Hybrid method was developed based on a need to generate accurate sensitivities for specified systems with CLUTCH. This new method provides improved sensitivities with HMF-028-001, specifically with 238 U in the large reflector region. With the importance of each voxel predetermined with the adjoint flux, the hybrid method is able to generate more accurate sensitivities. More testing is needed for other types of systems and materials (i.e., thermal and intermediate energy ranges and different moderators and reflectors). Initial results are very promising and continual development of the new hybrid method is currently in progress.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS1977

Methods of shield analysis for protection against electrons in space

It is anticipated that many future manned space operations will be radiation limited and that laminated wall structures and the use of new materials will be required to reduce radiation exposure. Methods for electron shield analysis are reviewed in light of anticipated needs in the space program. The most general method is still the Monte Carlo method, which is of limited usefulness for shield analysis due to excessive computer requirements. Methods based on energy deposition coefficients or energy transmission and reflection factors are quite accurate, but are currently limited to aluminum shield material. Analytical methods based on Mar's approximation for the electron transmission factor are relatively general and computer efficient but seriously underestimate shield requirements. A correction to methods using Mar's approximate transmission factor is derived herein and results in a slightly conservative estimate of shield requirements. Techniques for laminated shield design are still lacking.

Wilson, J. W.↗
NASA NTRS2009

A New Monte Carlo Filtering Method for the Diagnosis of Mission-Critical Failures

Testing large-scale systems is expensive in terms of both time and money. Running simulations early in the process is a proven method of finding the design faults likely to lead to critical system failures, but determining the exact cause of those errors is still time-consuming and requires access to a limited number of domain experts. It is desirable to find an automated method that explores the large number of combinations and is able to isolate likely fault points. Treatment learning is a subset of minimal contrast-set learning that, rather than classifying data into distinct categories, focuses on finding the unique factors that lead to a particular classification. That is, they find the smallest change to the data that causes the largest change in the class distribution. These treatments, when imposed, are able to identify the settings most likely to cause a mission-critical failure. This research benchmarks two treatment learning methods against standard optimization techniques across three complex systems, including two projects from the Robust Software Engineering (RSE) group within the National Aeronautics and Space Administration (NASA) Ames Research Center. It is shown that these treatment learners are both faster than traditional methods and show demonstrably better results.

Gay, Gregory↗
DOE OSTI2014

A stochastic analysis of steady and transient heat conduction in random media using a homogenization approach

We present a new stochastic analysis for steady and transient one-dimensional heat conduction problem based on the homogenization approach. Thermal conductivity is assumed to be a random field K consisting of random variables of a total number N. Both steady and transient solutions T are expressed in terms of the homogenized solution (symbol) and its spatial derivatives (equation), where homogenized solution (symbol) is obtained by solving the homogenized equation with effective thermal conductivity. Both mean and variance of stochastic solutions can be obtained analytically for K field consisting of independent identically distributed (i.i.d) random variables. The mean and variance of T are shown to be dependent only on the mean and variance of these i.i.d variables, not the particular form of probability distribution function of i.i.d variables. Variance of temperature field T can be separated into two contributions: the ensemble contribution (through the homogenized temperature (symbol)); and the configurational contribution (through the random variable Ln(x)Ln(x)). The configurational contribution is shown to be proportional to the local gradient of (symbol). Large uncertainty of T field was found at locations with large gradient of (symbol) due to the significant configurational contributions at these locations. Numerical simulations were implemented based on a direct Monte Carlo method and good agreement is obtained between numerical Monte Carlo results and the proposed stochastic analysis.

99 GENERAL AND MISCELLANEOUS↗