SEARCH · Engineering Papers
Results for “OLSON”
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.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
FFT, FMM, and multigrid on the road to exascale: Performance challenges and opportunities
FFT, FMM, and multigrid methods are widely used fast and highly scalable solvers for elliptic PDEs. However, emerging large-scale computing systems are introducing challenges in comparison to current petascale computers. Recent efforts (Dongarra et al. 2011) have identified several constraints in the design of exascale software that include massive concurrency, resilience management, exploiting the high performance of heterogeneous systems, energy efficiency, and utilizing the deeper and more complex memory hierarchy expected at exascale. In this paper, we perform a model-based comparison of the FFT, FMM, and multigrid methods in the context of these projected constraints. Finally, we use performance models to offer predictions about the expected performance on upcoming exascale system configurations based on current technology trends.
Effect of a Nitrogen-Doped PtRu/Carbon Anode Catalyst on the Durability of a Direct Methanol Fuel Cell
Abstract not provided
Effect of Nitrogen Post-Doping on a Commercial Platinum-Ruthenium/Carbon Anode Catalyst
Abstract not provided
Gray radiation transport models for three-dimensional binary stochastic media using effective opacities
Explore the source record for details and available documents.
Gray and multigroup radiation transport models for two-dimensional binary stochastic media using effective opacities
One-dimensional models for the transport of radiation through binary stochastic media do not work in multi-dimensions. In addition, authors have attempted to modify or extend the 1D models to work in multidimensions without success. Analytic one-dimensional models are successful in 1D only when assuming greatly simplified physics. State of the art theories for stochastic media radiation transport do not address multi-dimensions and temperature-dependent physics coefficients. Here, the concept of effective opacities and effective heat capacities is found to well represent the ensemble averaged transport solutions in cases with gray or multigroup temperature-dependent opacities and constant or temperature-dependent heat capacities. In every case analyzed here, effective physics coefficients fit the transport solutions over a useful range of parameter space. The transport equation is solved with the spherical harmonics method with angle orders of n=1 and 5. Although the details depend on what order of solution is used, the general results are similar, independent of angular order.
Gray and multigroup radiation transport through 3D binary stochastic media with different sphere radii distributions
Here, gray and multigroup radiation is transported through 3D media consisting of spheres randomly placed in a uniform background. Comparisons are made between using constant radii spheres and three different distributions of sphere radii. Because of the computational cost of 3D calculations, only the lowest angle order, n=1, is tested. If the mean chord length is held constant, using different radii distributions makes little difference. This is true for both gray and multigroup solutions. 3D transport solutions are compared to 2D and 1D solutions with the same mean chord lengths. 2D disk and 3D sphere media give solutions that are nearly identical while 1D slab solutions are fundamentally different.
Conditional Point Sampling: A Monte Carlo Method for Radiation Transport in Stochastic Media.
Current methods for stochastic media transport are either computationally expensive or, by nature, approximate. Moreover, none of the well-developed, benchmarked approximate methods can compute the variance caused by the stochastic mixing, a quantity especially important to safety calculations. Therefore, we derive and apply a new conditional probability function (CPF) for use in the recently developed stochastic media transport algorithm Conditional Point Sampling (CoPS), which 1) leverages the full intra-particle memory of CoPS to yield errorless computation of stochastic media outputs in 1D, binary, Markovian-mixed media, and 2) leverages the full inter-particle memory of CoPS and the recently developed Embedded Variance Deconvolution method to yield computation of the variance in transport outputs caused by stochastic material mixing. Numerical results demonstrate errorless stochastic media transport as compared to reference benchmark solutions with the new CPF for this class of stochastic mixing as well as the ability to compute the variance caused by the stochastic mixing via CoPS. Using previously derived, non-errorless CPFs, CoPS is further found to be more accurate than the atomic mix approximation, Chord Length Sampling (CLS), and most of memory-enhanced versions of CLS surveyed. In addition, we study the compounding behavior of CPF error as a function of cohort size (where a cohort is a group of histories that share intra-particle memory) and recommend that small cohorts be used when computing the variance in transport outputs caused by stochastic mixing.
A variance deconvolution estimator for efficient uncertainty quantification in Monte Carlo radiation transport applications
Monte Carlo simulations are at the heart of many high-fidelity simulations and analyses for radiation transport systems. As is the case with any complex computational model, it is important to propagate sources of input uncertainty and characterize how they affect model output. Unfortunately, uncertainty quantification (UQ) is made difficult by the stochastic variability that Monte Carlo transport solvers introduce. The standard method to avoid corrupting the UQ statistics with the transport solver noise is to increase the number of particle histories, resulting in very high computational costs. In this contribution, we propose and analyze a sampling estimator based on the law of total variance to compute UQ variance even in the presence of residual noise from Monte Carlo transport calculations. Here, we rigorously derive the statistical properties of the new variance estimator, compare its performance to that of the standard method, and demonstrate its use on neutral particle transport model problems involving both attenuation and scattering physics. We illustrate, both analytically and numerically, the estimator’s statistical performance as a function of available computational budget and the distribution of that budget between UQ samples and particle histories. We show analytically and corroborate numerically that the new estimator is unbiased, unlike the standard approach, and is more accurate and precise than the standard estimator for the same computational budget.
Emulation of radiation transport in 3D stochastic media using 1D planar Monte Carlo stochastic media radiation transport algorithms
A subset of stochastic media radiation transport problems involves those in which radiation is incident on a thin slab of stochastic material. Particle tracking in 3D for such problems is expensive, and 1D planar models lack accuracy because they only allow the material to change in one dimension. Therefore, we propose dimensional emulation, which through a slight modification allows existing 1D planar geometry stochastic media radiation transport models to reproduce results from the equivalent 3D models by allowing the material to change in all three dimensions, reproducing the fidelity of the 3D model for the low computational cost of the 1D planar model. In this work, we apply dimensional emulation to three Monte Carlo stochastic media radiation transport models: Chord Length Sampling (CLS), the Local Realization Preserving method (LRP), and a variant of Conditional Point Sampling (CoPS). For a common Markovian benchmark set, the 3D emulation variants of these algorithms are numerically verified to reproduce the results of the 3D variants within statistics while running 1.3 to 2 times faster in the implementation within Sandia National Laboratories open-source research code PlaybookMC. The 3D emulation variants are also shown to yield a 72%–92% reduction in error for the thin slab problems in comparison to the 1D benchmark. As a result, the 3D emulation variant of CLS and CoPS-1 are shown to reproduce 3D CLS results that were used to approximate results for a 3D spherical inclusion geometry benchmark set.
A rapid Orthopoxvirus purification protocol suitable for high-containment laboratories
Not Available
In situ high-temperature 3D imaging of the damage evolution in a SiC nuclear fuel cladding material
Silicon carbide (SiC)-based nuclear fission fuel rod cladding has been considered as one of the possible designs for accident tolerant fuels. It is in the form of a SiC fibre reinforced SiC matrix composite tube (SiC f -SiC m ) with monolithic SiC outer and/or inner coating layers. This study focuses on the deformation and fracture processes in this material using in situ X-ray micro-computed tomography (XCT) at room temperature (RT) and 1200 °C in an inert gas environment in a C-ring compression loading configuration. Prior to testing, local properties and residual stresses were characterised using nanoindentation and Raman spectroscopy since they can impact the mechanical behaviour of the material. The 3D strain distribution, crack formation and propagation processes including the toughening mechanisms (e.g., crack deflection, micro-cracking, crack bridging and bifurcation) are investigated in the coating and underlying composites at RT and 1200 °C. There is no particular sequence which toughening mechanism occurs first – this is very different from the conventional toughening theory in ceramic-matrix composites under uniaxial tension loading. Indeed, no evidence of fibre pull-out or fibre fracture was observed in this SiC f -SiC m nuclear cladding material in the current C-ring compression configuration. The correlation between local measurements and bulk mechanical behaviour are discussed.
Structural stability and electrochemical response of 3D printed and reactively sintered Ga-doped Li7La3Zr2O12 electrolytes
Not Available
Conversion of phosphoenolpyruvate to pyruvate in Thermoanaerobacterium saccharolyticum
Not Available
Expression and Characterization of Monofunctional Alcohol Dehydrogenase Enzymes in Clostridium thermocellum
Not Available
Engineering Clostridium thermocellum for production of 2,3-butanediol from cellulose
Clostridium thermocellum is a promising host for consolidated bioprocessing due to its ability to directly ferment cellulose into fuels and chemicals. However, natural product formation in this organism is limited. Here, we report engineering C. thermocellum for the production of 2,3-butanediol (23BD), a valuable industrial chemical. We functionally expressed a thermophilic 23BD pathway in this organism resulting in a 23BD titer of 19.7 mM from cellulose, representing a metabolic yield of 24%. We used a cell-free systems biology approach to identify limiting steps in the 23BD pathway, revealing that exogenous 23BD dehydrogenase (BDH) activity was essential for production, while native acetolactate synthase (ALS) and acetolactate decarboxylase (ALDC) activities were present but limiting in the parent strain. This approach also revealed redox balance limitations. We demonstrated that this improved understanding of redox balance limitations could be used to increase 23BD titer in vivo, showing that adding acetate could be used to increase 23BD yield. This work establishes a foundation for developing C. thermocellum into a robust platform for 23BD production directly from cellulose and highlights the utility of cell-free systems for guiding metabolic engineering in non-model organisms.