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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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LaCETS baseline flight study include: 29 high-quality nearfield shock structure probings at three Mach numbers; Shocks in exhaust plume measured; ! CFD study of simplified nozzle shows similar plume structures as flight data; ! Phase II flights scheduled for October 2008; and ! US Industry and Academia invited to participate in analysis, review, and assessment of LaNCETS data.
This paper is a multidisciplinary review of empirical, statistical learning from a graphical model perspective. Well-known examples of graphical models include Bayesian net- works, directed graphs representing a Markov chain, and undirected networks representing a Markov field. These graphical models are extended to model data analysis and empirical learning using the notation of plates. Graphical operations for simplifying and manipulating a problem are provided including decomposition, differentiation, and the manipulation of probability models from the exponential family. These operations adapt existing techniques from statistics and automatic differentiation to graphs. Two standard algorithm schemes for learning are reviewed in a graphical framework: Gibbs sampling and the expectation maximization algorithm. Some algorithms are developed in this graphical framework including a generalized version of linear regression, techniques for feed-forward networks, and learning Gaussian and discrete Bayesian networks from data. The paper concludes by sketching some implications for data analysis and summarizing some popular algorithms that fall within the framework presented. The main original contributions here are the decomposition techniques and the demonstration that graphical models provide a framework for understanding and developing complex learning algorithms.
The arithmetic Fourier transform (AFT) is a number-theoretic approach to Fourier analysis which has been shown to perform competitively with the classical FFT in terms of accuracy, complexity, and speed. Theorems developed in a previous paper for the AFT algorithm are used here to derive the original AFT algorithm which Bruns found in 1903. This is shown to yield an algorithm of less complexity and of improved performance over certain recent AFT algorithms. A VLSI architecture is suggested for this simplified AFT algorithm. This architecture uses a butterfly structure which reduces the number of additions by 25 percent of that used in the direct method.
Here, from within the umbrella of the Simplified Human Error Experimental Program (SHEEP) framework, this paper analyzes human performance differences between professional and student operators when using a simplified simulator (i.e., Rancor Microworld). This paper represents a crucial step in understanding the fidelity of the simplified simulators and student operators within the SHEEP study. This paper explores a randomized factorial experimental design that features two independent variables: participant type and event class. Six human performance measurements are considered in the experiment. The experiment is conducted using 20 professional reactor operators employed at actual nuclear power plants (NPPs), along with 20 trained students. The experimental data are analyzed via statistical analysis methods. Finally, this paper examines the differences in human performance between actual operators and students when using Rancor Microworld.
Rhodococcus opacus is a bacterium that has a high tolerance to aromatic compounds and can produce significant amounts of triacylglycerol (TAG). Here, we present iGR1773, the first genome-scale model (GSM) of R. opacus PD630 metabolism based on its genomic sequence and associated data. The model includes 1773 genes, 3025 reactions, and 1956 metabolites, was developed in a reproducible manner using CarveMe, and was evaluated through Metabolic Model tests (MEMOTE). We combine the model with two Constraint-Based Reconstruction and Analysis (COBRA) methods that use transcriptomics data to predict growth rates and fluxes: E-Flux2 and SPOT (Simplified Pearson Correlation with Transcriptomic data). Growth rates are best predicted by E-Flux2. Flux profiles are more accurately predicted by E-Flux2 than flux balance analysis (FBA) and parsimonious FBA (pFBA), when compared to 44 central carbon fluxes measured by 13C-Metabolic Flux Analysis (13C-MFA). Under glucose-fed conditions, E-Flux2 presents an R2 value of 0.54, while predictions based on pFBA had an inferior R2 of 0.28. We attribute this improved performance to the extra activity information provided by the transcriptomics data. For phenol-fed metabolism, in which the substrate first enters the TCA cycle, E-Flux2’s flux predictions display a high R2 of 0.96 while pFBA showed an R2 of 0.93. We also show that glucose metabolism and phenol metabolism function with similar relative ATP maintenance costs. These findings demonstrate that iGR1773 can help the metabolic engineering community predict aromatic substrate utilization patterns and perform computational strain design.
The X-29A advanced technology demonstrator flight envelope expansion program and the subsequent flight research phase gave impetus to the development of several innovative real-time analysis and display techniques. These new techniques produced significant improvements in flight test productivity, flight research capabilities, and flight safety. These techniques include real-time measurement and display of in-flight structural loads, dynamic structural mode frequency and damping, flight control system dynamic stability and control response, aeroperformance drag polars, and aircraft specific excess power. Several of these analysis techniques also provided for direct comparisons of flight-measured results with analytical predictions. The aeroperformance technique was made possible by the concurrent development of a new simplified in-flight net thrust computation method. To achieve these levels of on-line flight test analysis, integration of ground and airborne systems was required. The capability of NASA Ames Research Center, Dryden Flight Research Facility's Western Aeronautical Test Range was a key factor in enabling implementation of these methods.
The X-29A advanced technology demonstrator flight envelope expansion program and the subsequent flight research phase gave impetus to the development of several innovative real-time analysis and display techniques. These new techniques produced significant improvements in flight test productivity, flight research capabilities, and flight safety. These techniques include real-time measurement and display of in-flight structural loads, dynamic structural mode frequency and damping, flight control system dynamic stability and control response, aeroperformance drag polars, and aircraft specific excess power. Several of these analysis techniques also provided for direct comparisons of flight-measured results with analytical predictions. The aeroperformance technique was made possible by the concurrent development of a new simplified in-flight net thrust computation method. To achieve these levels of on-line flight test analysis, integration of ground and airborne systems was required. The capability of NASA Ames Research Center, Dryden Flight Research Facility's Western Aeronautical Test Range was a key factor to enable implementation of these methods.
The performance of two conceptually-simple uncertainty quantification techniques are tested against the rigorous nested-loop sampling technique of Roy and Oberkampf (Comput Methods Appl Mech Eng, 200: 2131–2144, 2011) (herein called full-sampling) using two very small-scale DEM-based models of particulate flow (one gas-solid flow and one granular flow). The first simplified forward uncertainty propagation technique, reduced-sampling, uses a sensitivity analysis to eliminate uncertain inputs that have little impact on the model output prior to nested-loop sampling. The second technique, boundary-sampling, uses a sensitivity analysis to inform the selection of two bounding cases for each key model output. In conclusion, the uncertainties in the model outputs obtained via the reduced- and boundary-sampling methods agree well with those from full-sampling for both the gas-solid and granular flow models while yielding computational savings of 65–75% (reduced sampling) and 94–97% (boundary sampling).
Fermionic asymmetric dark matter (ADM) can be captured in neutron stars (NSs) via scatterings with the star constituents. The absence of dark matter annihilation due to its asymmetric nature leads to ADM accumulation in the NS core, potentially reaching densities sufficient to exceed the Chandrasekhar limit and trigger its gravitational collapse into a black hole (BH), eventually consuming the NS from within. Therefore, the existence and observation of old neutron stars provide a means to constrain the properties of ADM. We revisit previous constraints on the mass and scattering cross section off neutrons of fermionic ADM across a class of models. We critically examine common simplifying approximations used in the literature to derive these limits. Our analysis includes improved treatments of dark matter capture, thermalization, BH formation, accretion, and evaporation. We find that previous results can be relaxed by a few orders of magnitude once these effects are properly accounted for.
Harmonic instability and associated oscillation events have become one of the main concerns in MMC-based HVdc systems. These oscillations can appear in the range from a few hundred hertz to several kilohertz, and the root cause is identified as delay-induced negative damping of MMC impedance appearing at the system resonance frequency. Here, this paper introduces a wideband impedance reshaping method through MMC control to eliminate such negative damping for both grid-following (GFL) and grid-forming (GFM) MMCs, which makes the MMC impedance completely passive from the second harmonic frequency upward, thus preventing all harmonic oscillations. First, simplified impedance models of MMCs are derived for the harmonic stability analysis and the impedance reshaping control design. Next, a passivity-based impedance reshaping method is presented, as well as practical considerations for its implementation. In addition, to maintain the MMC's disturbance ride-through capability, an adaptive activation scheme is developed, which enables the wideband impedance reshaping control only in the presence of harmonic oscillation events. The effectiveness of the proposed method is validated by frequency domain analysis and by electromagnetic transient (EMT) simulations of two typical MMC-based power systems.
Massively Parallel and Portable Genomic Sequence Analysis (mappgene) is a sequencing analysis workflow for high performance computing. It incorporates novel technologies to simplify and accelerate genetics research.
The study of microbiomes by sequencing has revealed a plethora of correlations between microbial community composition and various life-history characteristics of the corresponding host species. However, inferring causation from correlation is often hampered by the sheer compositional complexity of microbiomes, even in simple organisms. Synthetic communities offer an effective approach to infer cause-effect relationships in host-microbiome systems. Yet the available communities suffer from several drawbacks, such as artificial (thus non-natural) choice of microbes, microbe-host mismatch (e.g., human microbes in gnotobiotic mice), or hosts lacking genetic tractability. Here we introduce CeMbio, a simplified natural Caenorhabditis elegans microbiota derived from our previous meta-analysis of the natural microbiome of this nematode. The CeMbio resource is amenable to all strengths of the C. elegans model system, strains included are readily culturable, they all colonize the worm gut individually, and comprise a robust community that distinctly affects nematode life-history. Several tools have additionally been developed for the CeMbio strains, including diagnostic PCR primers, completely sequenced genomes, and metabolic network models. With CeMbio, we provide a versatile resource and toolbox for the in-depth dissection of naturally relevant host-microbiome interactions in C. elegans.
A preliminary failure mode, failure effect, and criticality analysis of the major subsystems of nuclear electric propulsion is presented. Simplified reliability block diagrams are also given. A computer program was used to calculate the reliability of the heat rejection subsystem.
Investigation of the effect of using plane quadrilateral membrane elements for modeling nonplanar structures. The effect is assessed by analyzing a simplified finite element model with the aid of the structure network analysis program. The results obtained indicate that the use of planar quadrilateral membrane elements for modeling bending problems can lead to large errors if the four points that define the quadrilateral are not in the same plane.
The fluid rheology model is used to investigate the traction behavior for typical traction drive contacts. The aspect ratio of the contact and the invariably present spin are investigated. Contacts with a low aspect ratio predict a superior performance in that they show less slip for the same degree of traction. Spin always has a diminishing effect on the traction at the same slip. At sufficiently high spin the model may be simplified to a limiting shear stress model. The conventional rigid plastic analysis applies here equally well.
Analysis of nonlinear plasma wave interactions is usually very complicated, and simplifying mathematical approaches are highly desirable. The application of averaged-Lagrangian methods offers a considerable reduction in effort, with improved insight into synchronism and conservation (Manley-Rowe) relations. This chapter indicates how suitable Lagrangian densities have been defined, expanded, and manipulated to describe nonlinear wave-wave and wave-particle interactions in the microscopic, macroscopic and cold plasma models. Recently, further simplifications have been introduced by the use of techniques derived from Lie algebra. These and likely future developments are reviewed briefly.
A simplified model of high-pressure spray combustion is examined. The analysis relies on a kappa-epsilon-g turbulence model in conjunction with the locally homogeneous flow (LHF) approximation of two-phase flow, which implies infinitely fast transport rates between the phases. High-pressure phenomena near the thermodynamic critical point are treated using the Redlich-Kwong equation of state. Predictions are compared with existing measurements of spray boundaries in a pressure-atomized n-pentane spray (Sauter mean diameter, approximately 30 microns) burning in stagnant air at 3, 6, and 9 MPa. The LHF model overestimates the rate of development of the flow, yielding spray lengths roughly 20% shorter than measured. Calibrated drop-life-history calculations suggest that finite interphase transport rates are the primary cause of the discrepancy.
An analytical procedure for predicting thrust chamber life is developed. The hot-gas-wall ligaments separating the coolant and combustion gas are subjected to pressure loading and severe thermal cycling. The resulting stresses interact during plastic straining causing incremental bulging of the ligaments during each firing cycle. This mechanism of plastic ratcheting is analyzed and a method using a yield surface for combined bending and membrane loading developed for determining the incremental permanent deflection and progressive thinning near the center of the ligaments. Fatigue and tensile instability are analyzed as possible failure modes. Results of the simplified analyses compare favorably with available experimental data and finite element analysis results for OFHC (Oxygen Free High Conductivity) copper. They are also in reasonably good agreement with experimental data for NARloy Z, a copper-zirconium-silver alloy developed by the Rocketdyne Division of Rockwell International.