93,238 research outputs found
Sensitivity Analysis of Process Parameters in Laser Deposition
In laser cladding with powder injection process, process output parameters, including
melt pool temperature and melt pool dimensions, are critical for part quality. This paper uses
simulation and experiments to investigate the effect of the process input parameters: laser power,
powder mass flow rate, and scanning speed on the output parameters. Numerical simulations and
experiments are conducted using a factorial design. The results are statistically analyzed to
determine the significant factors and their interactions. The simulation results are compared to
experimental results. The quantitative agreement/disagreement is discussed and further research is
outlined.Mechanical Engineerin
Enable High-resolution, Real-time Ensemble Simulation and Data Assimilation of Flood Inundation using Distributed GPU Parallelization
Numerical modeling of the intensity and evolution of flood events are
affected by multiple sources of uncertainty such as precipitation and land
surface conditions. To quantify and curb these uncertainties, an ensemble-based
simulation and data assimilation model for pluvial flood inundation is
constructed. The shallow water equation is decoupled in the x and y directions,
and the inertial form of the Saint-Venant equation is chosen to realize fast
computation. The probability distribution of the input and output factors is
described using Monte Carlo samples. Subsequently, a particle filter is
incorporated to enable the assimilation of hydrological observations and
improve prediction accuracy. To achieve high-resolution, real-time ensemble
simulation, heterogeneous computing technologies based on CUDA (compute unified
device architecture) and a distributed storage multi-GPU (graphics processing
unit) system are used. Multiple optimization skills are employed to ensure the
parallel efficiency and scalability of the simulation program. Taking an urban
area of Fuzhou, China as an example, a model with a 3-m spatial resolution and
4.0 million units is constructed, and 8 Tesla P100 GPUs are used for the
parallel calculation of 96 model instances. Under these settings, the ensemble
simulation of a 1-hour hydraulic process takes 2.0 minutes, which achieves a
2680 estimated speedup compared with a single-thread run on CPU. The
calculation results indicate that the particle filter method effectively
constrains simulation uncertainty while providing the confidence intervals of
key hydrological elements such as streamflow, submerged area, and submerged
water depth. The presented approaches show promising capabilities in handling
the uncertainties in flood modeling as well as enhancing prediction efficiency
Fast, Exact Bootstrap Principal Component Analysis for p>1 million
Many have suggested a bootstrap procedure for estimating the sampling
variability of principal component analysis (PCA) results. However, when the
number of measurements per subject () is much larger than the number of
subjects (), the challenge of calculating and storing the leading principal
components from each bootstrap sample can be computationally infeasible. To
address this, we outline methods for fast, exact calculation of bootstrap
principal components, eigenvalues, and scores. Our methods leverage the fact
that all bootstrap samples occupy the same -dimensional subspace as the
original sample. As a result, all bootstrap principal components are limited to
the same -dimensional subspace and can be efficiently represented by their
low dimensional coordinates in that subspace. Several uncertainty metrics can
be computed solely based on the bootstrap distribution of these low dimensional
coordinates, without calculating or storing the -dimensional bootstrap
components. Fast bootstrap PCA is applied to a dataset of sleep
electroencephalogram (EEG) recordings (, ), and to a dataset of
brain magnetic resonance images (MRIs) ( 3 million, ). For the
brain MRI dataset, our method allows for standard errors for the first 3
principal components based on 1000 bootstrap samples to be calculated on a
standard laptop in 47 minutes, as opposed to approximately 4 days with standard
methods.Comment: 25 pages, including 9 figures and link to R package. 2014-05-14
update: final formatting edits for journal submission, condensed figure
Towards quantification of condition monitoring benefit for wind turbine generators
Condition monitoring systems are increasingly installed in wind turbine generators with the goal of providing component-specific information to the wind farm operator and hence increase equipment availability through maintenance and operating actions based on this information. In some cases, however, the economic benefits of such systems are unclear. A quantitative measure of these benefits may therefore be of value to utilities and O&M groups involved in planning and operating wind farm installations. The development of a probabilistic model based on discrete-time Markov Chain solved via Monte Carlo methods to meet these requirements is illustrated. Potential value is demonstrated through case study simulations
The cosmic-ray positron energy spectrum measured by PAMELA
Precision measurements of the positron component in the cosmic radiation
provide important information about the propagation of cosmic rays and the
nature of particle sources in our Galaxy. The satellite-borne experiment PAMELA
has been used to make a new measurement of the cosmic-ray positron flux and
fraction that extends previously published measurements up to 300 GeV in
kinetic energy. The combined measurements of the cosmic-ray positron energy
spectrum and fraction provide a unique tool to constrain interpretation models.
During the recent solar minimum activity period from July 2006 to December 2009
approximately 24500 positrons were observed. The results cannot be easily
reconciled with purely secondary production and additional sources of either
astrophysical or exotic origin may be required.Comment: 14 pages, 4 figures, 1 table. Accepted for publication in Physical
Review Letters. Corrected a typo in the flux units of Table
- …