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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 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2013

Dosimetric impact of Acuros XB deterministic radiation transport algorithm for heterogeneous dose calculation in lung cancer

Purpose: The novel deterministic radiation transport algorithm, Acuros XB (AXB), has shown great potential for accurate heterogeneous dose calculation. However, the clinical impact between AXB and other currently used algorithms still needs to be elucidated for translation between these algorithms. The purpose of this study was to investigate the impact of AXB for heterogeneous dose calculation in lung cancer for intensity-modulated radiation therapy (IMRT) and volumetric-modulated arc therapy (VMAT). Methods: The thorax phantom from the Radiological Physics Center (RPC) was used for this study. IMRT and VMAT plans were created for the phantom in the Eclipse 11.0 treatment planning system. Each plan was delivered to the phantom three times using a Varian Clinac iX linear accelerator to ensure reproducibility. Thermoluminescent dosimeters (TLDs) and Gafchromic EBT2 film were placed inside the phantom to measure delivered doses. The measurements were compared with dose calculations from AXB 11.0.21 and the anisotropic analytical algorithm (AAA) 11.0.21. Two dose reporting modes of AXB, dose-to-medium in medium (D{sub m,m}) and dose-to-water in medium (D{sub w,m}), were studied. Point doses, dose profiles, and gamma analysis were used to quantify the agreement between measurements and calculations from both AXB and AAA. The computation times for AAA and AXB were also evaluated. Results: For the RPC lung phantom, AAA and AXB dose predictions were found in good agreement to TLD and film measurements for both IMRT and VMAT plans. TLD dose predictions were within 0.4%-4.4% to AXB doses (both D{sub m,m} and D{sub w,m}); and within 2.5%-6.4% to AAA doses, respectively. For the film comparisons, the gamma indexes ({+-}3%/3 mm criteria) were 94%, 97%, and 98% for AAA, AXB{sub Dm,m}, and AXB{sub Dw,m}, respectively. The differences between AXB and AAA in dose-volume histogram mean doses were within 2% in the planning target volume, lung, heart, and within 5% in the spinal cord. However, differences up to 8% between AXB and AAA were found at lung/soft tissue interface regions for individual IMRT fields. AAA was found to be 5-6 times faster than AXB for IMRT, while AXB was 4-5 times faster than AAA for VMAT plan. Conclusions: AXB is satisfactorily accurate for the dose calculation in lung cancer for both IMRT and VMAT plans. The differences between AXB and AAA are generally small except in heterogeneous interface regions. AXB D{sub w,m} and D{sub m,m} calculations are similar inside the soft tissue and lung regions. AXB can benefit lung VMAT plans by both improving accuracy and reducing computation time.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

SU-F-T-111: Investigation of the Attila Deterministic Solver as a Supplement to Monte Carlo for Calculating Out-Of-Field Radiotherapy Dose

Purpose: To use the Attila deterministic solver as a supplement to Monte Carlo for calculating out-of-field organ dose in support of epidemiological studies looking at the risks of second cancers. Supplemental dosimetry tools are needed to speed up dose calculations for studies involving large-scale patient cohorts. Methods: Attila is a multi-group discrete ordinates code which can solve the 3D photon-electron coupled linear Boltzmann radiation transport equation on a finite-element mesh. Dose is computed by multiplying the calculated particle flux in each mesh element by a medium-specific energy deposition cross-section. The out-of-field dosimetry capability of Attila is investigated by comparing average organ dose to that which is calculated by Monte Carlo simulation. The test scenario consists of a 6 MV external beam treatment of a female patient with a tumor in the left breast. The patient is simulated by a whole-body adult reference female computational phantom. Monte Carlo simulations were performed using MCNP6 and XVMC. Attila can export a tetrahedral mesh for MCNP6, allowing for a direct comparison between the two codes. The Attila and Monte Carlo methods were also compared in terms of calculation speed and complexity of simulation setup. A key perquisite for this work was the modeling of a Varian Clinac 2100 linear accelerator. Results: The solid mesh of the torso part of the adult female phantom for the Attila calculation was prepared using the CAD software SpaceClaim. Preliminary calculations suggest that Attila is a user-friendly software which shows great promise for our intended application. Computational performance is related to the number of tetrahedral elements included in the Attila calculation. Conclusion: Attila is being explored as a supplement to the conventional Monte Carlo radiation transport approach for performing retrospective patient dosimetry. The goal is for the dosimetry to be sufficiently accurate for use in retrospective epidemiological investigations.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Field-free deterministic switching of all–van der Waals spin-orbit torque system above room temperature

Two-dimensional van der Waals (vdW) magnetic materials hold promise for the development of high-density, energy-efficient spintronic devices for memory and computation. Recent breakthroughs in material discoveries and spin-orbit torque control of vdW ferromagnets have opened a path for integration of vdW magnets in commercial spintronic devices. However, a solution for field-free electric control of perpendicular magnetic anisotropy (PMA) vdW magnets at room temperatures, essential for building compact and thermally stable spintronic devices, is still missing. Here, we report a solution for the field-free, deterministic, and nonvolatile switching of a PMA vdW ferromagnet, Fe 3 GaTe 2 , above room temperature (up to 320 K). We use the unconventional out-of-plane anti-damping torque from an adjacent WTe 2 layer to enable such switching with a low current density of 2.23 × 10 6 A cm –2 . This study exemplifies the efficacy of low-symmetry vdW materials for spin-orbit torque control of vdW ferromagnets and provides an all-vdW solution for the next generation of scalable and energy-efficient spintronic devices.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2011

Deterministic methods for numerical simulation of high-energy runaway electron avalanches

The possibilities of two deterministic methods for describing the kinetics of high-energy runaway electrons (REs) are analyzed as alternatives to stochastic methods requiring unrealistically large computing resources in problems of numerical simulation of electric discharges in dense gases involving REs. One of the methods being developed in recent years is based on multigroup equations for the moments of the electron distribution function, while the second method, which is conventionally used to solve problems in gas discharges, is based on the diffusion-drift equation. The modern method of multigroup equations allows one to calculate the RE energy distribution and the spatial RE distribution along the electric force, which are close to these distributions obtained by the Monte Carlo method if the number N of energy groups is chosen properly. The diffusion-drift equation does not give the energy distribution, but its advantage is the possibility of obtaining spatial RE distributions using small computing resources not only along but also perpendicular to the electric force, which are close to those calculated by the Monte Carlo method. To simulate discharges by the method of multigroup equations, it is necessary to know a priori the number N of groups providing good accuracy, the characteristic RE multiplication time t{sub e}, and the energy runaway threshold {epsilon}{sub th} as functions of the electric-field overvoltage. The diffusion-drift equation requires the specification, along with t{sub e}, of the directed RE velocity and longitudinal and transverse diffusion coefficients calculated by the Monte Carlo method.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2016

Comparison of statistical and deterministic frameworks of uncertainty quantification

Two different approaches to the prediction problem are compared employing a realistic example— combustion of natural gas—with 102 uncertain parameters and 76 quantities of interests. One approach, termed bound-to-bound data collaboration (abbreviated to B2B), deploys semidefinite programming algorithms where the initial bounds on unknowns are combined with initial bounds of experimental data to produce new uncertainty bounds for the unknowns that are consistent with the data and, finally, deterministic uncertainty bounds for prediction in new settings. The other approach is statistical and Bayesian, referred to as BCP (for Bayesian calibration and prediction). It places prior distributions on the unknown parameters and on the parameters of the measurement error distributions and produces posterior distributions for model parameters and posterior distributions for model predictions in new settings. The predictions from the two approaches are consistent; a very large degree of overlap exists between B2B bounds and the support of the BCP predictive distribution. Interpretation and comparison of the results is closely connected with assumptions made about the model and experimental data and how they are used in both settings. As a result, the principal conclusion is that use of both methods protects against possible violations of assumptions in the BCP approach and conservative specifications and predictions using B2B.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

static-subid: Deterministic subordinate UID/GID assignment for unprivileged containers

static-subid calculates predictable subordinate UID and GID ranges for Linux users based on their UID, ensuring consistent ID mappings across multiple systems. Unlike shadow-utils' sequential allocation (which depends on creation order), static-subid uses a deterministic formula that guarantees the same user UID always receives the same subordinate ID range. Subordinate IDs enable user namespaces for unprivileged container runtimes (Podman, Docker rootless mode, LXC) by mapping container UIDs/GIDs to host subordinate IDs without requiring root privileges.

Riehecky, Pat [Fermi National Accelerator Laborato↗
DOE OSTI2022

Development of a three-dimensional APOLLO3 neutrons deterministic scheme for the CABRI reactor

CABRI is an experimental reactor to study the fuel behavior during reactivity injection transients. These transients being highly multiphysics, the development of suitable modeling and simulation tools to simulate them is important for the optimization of the tests and the control of the experimental conditions. This paper focuses on the development of an APOLLO3 deterministic core calculation tool dedicated to the CABRI transient analysis. It represents the first stage of the incremental process for the implementation of a multiphysics time-dependent modeling of the CABRI transient. The neutron calculation scheme is based on a classical two-step approach. The first step consists of a 281-energy group calculation flux with the TDT-MOC (Method Of Characteristics) solver for cross-section space and energy (23 groups) collapsing for the CABRI different assembly clusters. The bias on a 2D core neutron calculation due to the self-shielding calculation and collapsing on a restricted pattern are investigated thanks to a comparison with a direct full 2D calculation on a quarter of core. The second step relies on a pin-resolved transport 3D transport core calculation with the SN solver MINARET. A progressive numerical validation process is followed to quantify the calculation biases on reactivity and reaction rates at each step using reference calculations with the stochastic code TRIPOLI4. The next development stage toward a multiphysics scheme will be the implementation of the 3D-kinetics equation resolution and the coupling with a core thermal-hydraulics model. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2018

Validation of Deterministic Broadband Ground Motion and Variability from Dynamic Rupture Simulations of Buried Thrust Earthquakes

According to the article, we numerically model broadband ground motion (up to 5–7.5 Hz⁠) from blind‐thrust scenario earthquakes matching the fault geometry of the 1994 Mw 6.7 Northridge earthquake. Several realizations are modeled (by varying the hypocenter location in the dynamic rupture simulation) in a 1D‐layered velocity profile. In addition, we include Q(f )⁠, nonlinear effects from Drucker–Prager plasticity, and superimpose small‐scale medium complexity in both a 1D‐layered and 3D velocity model within the subsequent wave propagation. We investigate characteristics of the ground motion and its variability up to 50 km from the fault by comparing them with ground‐motion prediction equations (GMPEs), simple proxy metrics, as well as strong ground motion records from the Northridge event. We find that median ground motion closely follows the trend predicted by GMPEs and that the intraevent standard deviation, although varying with hypocenter location, lies near that of GMPE models. Plasticity affects ground‐motion amplitudes in regions near the source, reducing intraevent variability above ∼0.5 Hz⁠. Heterogeneity in the velocity structure on both the regional and small scales is needed for the simulated data to match two proxy metrics: the period‐to‐period correlation of spectral acceleration (SA) and the ratio of maximum‐to‐median SA. Although small‐scale heterogeneity has a negligible effect on median SA for this style of rupture, it serves to significantly increase the cumulative absolute velocity, better agreeing with observations. When compared with strong‐motion data, we find that long‐wavelength velocity structure within our deterministic simulations reduces bias at both short and long periods. Finally, synthetic ground motion at both footwall and hanging‐wall sites has no clear dependence on the distance to rupture (at both short and long periods); directivity is likely overpowering any hanging‐wall effect.

Geochemistry & Geophysics↗
DOE OSTI2020

Deterministic and Statistical Modeling of a New Thermal Breakout Technology for Measuring the Maximum Horizontal In-Situ Stress

The current state-of-the-art technology for in-situ stress measurements involves an integrated approach that combines borehole breakout observations, drilling-induced tensile fractures, and hydraulic fracturing tests (i.e., “mini-fracs”). This methodology has achieved wide application in the oil and gas industry but has several limitations that often prevent successful in-situ stress measurements. One major limitation is that breakouts do not appear in all boreholes and are generally only a natural occurrence that cannot easily be controlled. Because borehole breakouts are used to directly measure the maximum horizontal in-situ stress magnitude, the absence of borehole breakouts presents a major data gap for in-situ stress measurements. In response to this data gap, a new US Department of Energy (US DOE)-sponsored thermal breakout technology that will provide a method for thermally inducing borehole breakouts and allow the consistent measurement of the maximum horizontal stress magnitude is currently in development. This thermal breakout technology involves heating the borehole and increasing the thermoelastic compressive stress in the rock until a breakout develops, which can be directly correlated to the maximum horizontal stress magnitude. The first step in this project was an analytical modeling study of the thermal breakout process. Based on the Kirsch solution (Kirsch 1898), a deterministic and statistical analysis was performed on the pertinent parameters that influence the maximum horizontal stress calculation. As a result of the analysis, the findings indicate that the thermal breakout technology is feasible and provides improved accuracy and/or an enhanced ability to measure the maximum horizontal stress. Future work as part of this US DOE-sponsored project includes additional validation through more detailed numerical modeling, laboratory testing, and field testing of the thermal breakout technology.

58 GEOSCIENCES↗
DOE OSTI2013

Verification & Validation of High-Order Short-Characteristics-Based Deterministic Transport Methodology on Unstructured Grids

The research team has developed a practical, high-order, discrete-ordinates, short characteristics neutron transport code for three-dimensional configurations represented on unstructured tetrahedral grids that can be used for realistic reactor physics applications at both the assembly and core levels. This project will perform a comprehensive verification and validation of this new computational tool against both a continuous-energy Monte Carlo simulation (e.g. MCNP) and experimentally measured data, an essential prerequisite for its deployment in reactor core modeling. Verification is divided into three phases. The team will first conduct spatial mesh and expansion order refinement studies to monitor convergence of the numerical solution to reference solutions. This is quantified by convergence rates that are based on integral error norms computed from the cell-by-cell difference between the code’s numerical solution and its reference counterpart. The latter is either analytic or very fine- mesh numerical solutions from independent computational tools. For the second phase, the team will create a suite of code-independent benchmark configurations to enable testing the theoretical order of accuracy of any particular discretization of the discrete ordinates approximation of the transport equation. For each tested case (i.e. mesh and spatial approximation order), researchers will execute the code and compare the resulting numerical solution to the exact solution on a per cell basis to determine the distribution of the numerical error. The final activity comprises a comparison to continuous-energy Monte Carlo solutions for zero-power critical configuration measurements at Idaho National Laboratory’s Advanced Test Reactor (ATR). Results of this comparison will allow the investigators to distinguish between modeling errors and the above-listed discretization errors introduced by the deterministic method, and to separate the sources of uncertainty.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2018

A Deterministic and Probabilistic Framework for Forecasting of Time-Series Damage States and Associated End-of-lIfe of a Pressurizer Water Reactor Surge Line under Design-Basis and Grid-Load-Following Loading Conditions

Argonne National Laboratory in support of the Department of Energy’s Light Water Reactor Sustainability (LWRS) program. The present semi-annual report covers the period between May 2018 and September 2018. In this report, we present the work performed to further improve the capability for structural integrity prediction. Part of this work focused on validating a computational fluid dynamics model for modeling thermal stratification. We also present finite element (FE) model based thermal-mechanical stress analysis of a pressurized water reactor (PWR) surge line under grid-load-following loading condition. In addition, we present work related to end-of-life prediction of a PWR surge line based on ASME code and NUREG-6909 deterministic approaches under design-basis and grid-load-following conditions. Our research in this report period also majorly involved with the development of a strategy for probabilistic fatigue life estimation. First, we applied a Weibull probabilistic modeling approach based on end-of-life fatigue data (traditional S~N data under in-air and PWR water conditions) to estimate the probabilistic life for a given strain amplitude. Second, we developed a data analytics based Markov-Chain-Monte-Carlo (MCMC) model for probabilistic modeling of time-series fatigue damage states and the associated probabilistic end-of-life of a component. Unlike the Weibull type approach, the MCMC type may not require a large number of fatigue tests for estimating the end-of-life for given loading and environmental conditions. We demonstrated the use of this framework through symmetric fatigue tests (stress- or strain-ontrolled tests either under in-air or PWR-water conditions) obtained from our earlier experiments. The MCMC model can use base time-series data either obtained from a model or fatigue experiment. Since experimental data are typically more accurate than model-calculated data, we used experiment-based time-series data to demonstrate the MCMC framework. However, when performing a complex experiment is not possible (due to time and costs involved), a model-based approach can be used to generate the time-series data. Similar model-based data are presented in our earlier report (e.g. for cyclic hardening damage states of a PWR surge line under constant amplitude and design-basis loading [1]). However, for the MCMC work in this report, we used experiment-based time-series damage states obtained from fatigue experiments under design-basis and grid-load-following loading conditions. The experimental loading inputs were based on thermal-mechanical FE model results of a typical PWR surge line. Then, we used the experimental time-series damage state data for forecasting the probabilistic time-series damage states and end-of-life of the PWR surge line. Based on this MCMC modeling strategy, and with the assumed loading, environment and thermal-mechanical boundary conditions, we have estimated that a 316SS-pure base metal PWR surge line would survive at least 159 years with zero failure probability.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2016

Deterministic Calculation of Gamma-Ray Transport Spectra with InterScatter.

Gamma-ray transport describes the way in which high-energy photons interact with matter. There are many well established, general purpose gamma transport calculation frameworks (such as GEANT4, MCNP, PARTISN, and GADRAS) that allow for complex generalized calculations, but they are typically not designed to be integrated into other multi-process, multi-platform applications, not designed for rapid computation, or their complexity leads to user errors. In this report, we introduce InterScatter: a deterministic simulation designed to quickly and easily calculate gamma-ray transport spectra for a 1D shielding geometry.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2016

Deterministic Calculation of Gamma-Ray Transport Spectra with InterScatter

Gamma-ray transport describes the way in which high-energy photons (gamma rays and x-rays) interact with matter. There are many well established, general purpose gamma transport calculation frameworks (such as GEANT4, MCNP, PARTISN, and GADRAS [1] [2] [3] [4]) that allow for complex generalized calculations, but they are typically not designed to be integrated into other multi-process, multi-platform applications, not designed for rapid computation, or their complexity leads to user errors. In this report, we introduce InterScatter: a deterministic simulation designed to quickly and easily calculate gamma-ray transport spectra for a 1D shielding geometry.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

A Hybrid Method for Tensor Decompositions that Leverages Stochastic and Deterministic Optimization

In this paper, we propose a hybrid method that uses stochastic and deterministic search to compute the maximum likelihood estimator of a low-rank count tensor with Poisson loss via state-of-theart local methods. Our approach is inspired by Simulated Annealing for global optimization and allows for fine-grain parameter tuning as well as adaptive updates to algorithm parameters. We present numerical results that indicate our hybrid approach can compute better approximations to the maximum likelihood estimator with less computation than the state-of-the-art methods by themselves.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Deterministic Transport: An Introduction [Slides]

In this lecture, we cover deterministic particle transport. We focus on neutral particles (neutrons, gamma-rays, thermal photons). Our goal is to predictively and accurately model how free particles interact with their environments and properties of systems involving those particles.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Deterministic and Monte Carlo Nuclear Data Adjustment Methods [Slides]

For the Bayesian Monte Carlo methodology, a need to understand convergence of the posterior moments as a function of the number of parameter realizations is required. In high-dimensional systems, it can be very costly to sample entire parameter space and perform functional evaluation for every realization. Bayesian Monte Carlo allows one to relax the GLLS approximations of model linearity and prior/posterior PDF shape. The Bayesian Stochastic Collocation Method is a deterministic approach to “sample” the parameter space. It allows one to relax the GLLS approximations of model linearity and posterior PDF shape. Higher-order posterior moments (i.e., skewness, kurtosis, etc.) can be studied through polynomial expansion. Tensor product quadrature scales poorly and can use sparse grid quadrature methods.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Deterministic Transport: An Introduction [Slides]

In this lecture, we cover deterministic particle transport. We focus on neutral particles (neutrons, gamma-rays, and thermal photons). Our goal is to predictively and accurately model how free particles interact with their environments and properties of systems involving those particles.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗